extfieldsofstudy: Biology Medicine

text:
Genome-wide identification of C2H2 zinc-finger genes and their expression patterns under heat stress in tomato (Solanum lycopersicum L.)

The C2H2 zinc finger protein (C2H2-ZFP) transcription factor family regulates the expression of a wide variety of genes in response to various developmental processes or abiotic stresses; however, these proteins have not yet been comprehensively analyzed in tomato (Solanum lycopersicum). In this study, a total of 104 C2H2-ZFs were identified in an uneven distribution across the entire tomato genome, and include seven segmental duplication events. Based on their phylogenetic relationships, these genes were clustered into nine distinct categories analogous to those in Arabidopsis thaliana. High similarities were found between the exon–intron structures and conserved motifs of the genes within each group. Correspondingly, the expression patterns of the C2H2-ZF genes indicated that they function in different tissues and at different developmental stages. Additionally, quantitative real-time PCR (qRT-PCR) results demonstrated that the expression levels of 34 selected C2H2-ZFs are changed dramatically among the roots, stems, and leaves at different time points of a heat stress treatment, suggesting that the C2H2-ZFPs are extensively involved in the heat stress response but have potentially varying roles. These results form the basis for the further molecular and functional analysis of the C2H2-ZFPs, especially for those members that significantly varied under heat treatment, which may be targeted to improve the heat tolerance of tomato and other Solanaceae species.

The first plant-specific C2H2 protein (ZPT2-1, renamed from EPF1) was identified in Petunia, and was found to interact with promoter region of the gene encoding 5-enolpyruvylshi-kimate-3-phosphate synthase (Takatsuji et al., 1992). Since then, the structures and functions of the plant C2H2-ZFPs have been widely reported, and shown to be involved in a variety of processes, including plant growth and development and the response to stresses (Huang et al., 2009;Iida et al., 2000;Kim et al., 2016;Sun et al., 2010;Wang et al., 2016). In Arabidopsis, the overexpression of zinc finger of Arabidopsis thaliana 12 (ZAT12) improved osmotic stress tolerance, and also interacted with ZAT7 or ZAT10 to enhance tolerance to salinity (Li et al., 2018;Mittler et al., 2006;Sholpan et al., 2005;Sultan et al., 2007). The AZF1 (Arabidopsis zinc-finger protein 1), AZF3, and STZ (salt tolerance zinc finger genes) are associated with the cold-stress response in Arabidopsis (Sakamoto et al., 2000), while ZAT18 was found to positively modulate drought-stress tolerance (Yin et al., 2017). In rice, the C2H2-ZFPs play a role in many aspects of stress tolerance, regulating the responses to cold, drought, oxidative, and salt stresses (Huang et al., 2009;Sun et al., 2010;Xu et al., 2008;Zhang et al., 2014). The functions of the C2H2-ZFPs in many other plants have also been reported, and are often found to be involved in plant development processes such as morphogenesis of cell and trichomes, ripening and senescence (Chang et al., 2018;Moreau et al., 2018;Weng et al., 2015), and stress resistance such as aluminum, drought and salt (Atreyee et al., 2018;Li et al., 2018;Rai, Singh & Shah, 2012). These findings showed that the C2H2-ZFPs are active in multiple physiological processes under stress conditions; however, the functions of the majority of the C2H2-ZFPs in tomato have not been reported.
Tomato is considered a model system for the study of both fleshy fruit development and the biology of the Solanaceae species (The Tomato Genome, 2012), and is resistant to a wide range of abiotic stress conditions (Yáñez et al., 2009). Previous studies have revealed that the C2H2-ZFPs play important roles in the defense and acclimation responses of plants to various environmental stress conditions (Wang et al., 2018); therefore, it is important to complete the genome-wide identification and expression analysis of the tomato C2H2-ZF family to better understand their roles in stress responses. Here, we identify 104 C2H2-ZFs in tomato and provide a comprehensive analysis of their phylogenetic relationships, genomic locations, and gene structures. Furthermore, the expression profiles of this gene family were analyzed in different tissues and under high temperature stress using data from heatmaps and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) analyses. This enabled us to reveal the transcriptional regulatory mechanisms of the C2H2-ZFs in tomato, and will provide valuable information for future cloning and functional studies of these genes in tomato and other Solanaceae species.

Genome-wide analysis of the C2H2-ZF family in tomato
The tomato C2H2-ZFP family members were identified using their homology to the Arabidopsis thaliana C2H2-ZFP sequences from the TAIR10 database (File S1). The tomato genome (The Tomato Genome, 2012) and protein sequences (https: //solgenomics.net/organism/Solanum_lycopersicum/genome) were used to construct a local protein database using Geneious v4.8.5 software (http://www.geneious.com/; Biomatters, Auckland, New Zealand), which was then BLASTP searched using the sequences of the A. thaliana C2H2-ZFPs (obtained from the Arabidopsis Information Resource; TAIR10, https://www.arabidopsis.org) as queries, with an E-value cut-off ≤ 1 × 10 −20 . Subsequently, the Hidden Markov Model (HMM) profiles of the C2H2-ZFP sequences (Pfam ID: PF00096) were downloaded from the Pfam database (http://pfam.xfam.org) and used to validate the identity of all candidate C2H2-ZF gene members.
All the obtained C2H2-ZFP sequences were further confirmed using the NCBI Conserved Domain Database (CDD; https://www.ncbi.nlm.nih.gov/cdd/) with the default parameters. Proteins without C2H2-ZF domains were removed. The locus ID and chromosomal location information of each tomato C2H2-ZF gene family member were obtained from the genome annotation file (File S1), and the lengths of the coding sequences (CDSs) were determined by performing BLASTn searches against the Sol Genomics Network database (https://solgenomics.net). The physicochemical properties of the deduced proteins, including the molecular weight (MW), isoelectric point (pI), and grand average of hydropathy (GRAVY) values, were determined using the ExPASy-ProtParam tool (http://web.expasy.org/protparam/).

Phylogenetic analysis and gene duplication
To identify the evolutionary relationships of the C2H2-ZF gene family members, all C2H2-ZFP sequences were aligned using ClustalW2 software under the default settings (Larkin et al., 2007). The aligned sequences were then subjected to a phylogenetic analysis using MEGA v6.0 (Tokyo Metropolitan University, Tokyo, Japan; Tamura et al., 2013). Subsequently, we compared the phylogenetic trees constructed and tested by different methods, including Maximum Likelihood (ML), Neighbor Joining (NJ), unweighted pairgroup method with arithmetic means (UPGMA) and Maximum Parsimony (MP) methods, respectively. The phylogenetic trees were constructed using different methods with 1,000 replicate bootstrap tests. The ML trees was calculated using the ProtML program under the JTT model (Guo et al., 2008), NJ trees was obtained using the JTT+I+G substitution model (Pan et al., 2018), UPGMA and MP trees were generated in MEGA v6.0 (Tamura et al., 2013) with the default parameters. Finally, the phylogenetic trees were visualized using FigTree v1.4.2 (http://tree.bio.ed.ac.uk/software/figtree/).
Based on the GFF genome files from the Sol Genomics Network database (https: //solgenomics.net; The Tomato Genome, 2012), a map of the distribution of the C2H2-ZF genes was drawn for each chromosome using MapChart v2.0 (Voorrips, 2002).

Gene structure, conserved motif and functional annotation analyses
Genome DNA and the corresponding CDSs of the putative C2H2-ZF genes were obtained from the Sol Genomics Network database (https://solgenomics.net; The Tomato Genome, 2012), then analyzed using the Gene Structure Display Server (GSDS v2.0; http://gsds.cbi.pku.edu.cn/index.php) to obtain information on the exon/intron structures. MEME v5.0.3 (http://meme-suite.org/tools/meme) was used to predict the corresponding conserved motifs (Bailey et al., 2009) with the following parameters: optimum motif widths of 6-300 residues, any repetition, and a maximum of 10 motifs (Pan et al., 2018). Each motif with an E-value <1 × 10 −10 was retained for motif detection. In addition, gene ontology analysis of tomato C2H2 family genes was performed using the Blast2GO program (Conesa et al., 2005) with the default parameters.

Expression analysis of the C2H2-ZF family members
The expression profiles of the C2H2-ZF genes were measured using the publicly available tomato RNA-Seq datasets retrieved from the TomExpress database v17.0.0 (Available online: http://tomexpress.toulouse.inra.fr/; Zouine et al., 2017). Subsequently, the expression levels had been normalized in tomato as the published method (Maza et al., 2013), and the pipeline was described below. The reads were mapped to the tomato genomes SL2.40 by the TopHat 2.0.0 software with default parameters (The Tomato Genome, 2012;Trapnell et al., 2012). Gene expression levels were assessed with Cufflinks software with default parameters and using the tomato gene annotation file ITAG3.2 (The Tomato Genome, 2012;Trapnell et al., 2012). Eventually, the visualized heatmaps were generated using Heatmap Illustrator 1.0.

Plant materials and heat treatment
The wild-type tomato (Solanum lycopersicum cv. Ailsa Craig) was grown in 15-cm pots containing a soil mix of humus, vermiculite, and perlite in a ratio of 3:1:1. The plants were grown under standard glasshouse conditions (16 h light and 8 h dark at 25 ± 2 • C). After one month of cultivation, the plants were subjected to a heat stress condition (42 • C) for 12 h or 24 h, while those collected at 0 h were used as the controls. All samples (leaves, stems, and roots) were collected and immediately frozen in liquid nitrogen for RNA extraction. Three biological repetitions were performed for each treatment.

RNA isolation and qRT-PCR analysis
Total RNA was isolated from the roots, stems, and leaves using the RNAiso Plus Kit (TaKaRa Bio, Dalian, China). 1-µg aliquot of RNA was treated with DNase I (Takara Bio, Dalian, China) and transcribed into cDNA using the Oligo dT-Adaptor Primers and an RNA PCR Kit (AMV) v3.0 (Takara Bio, Dalian, China). The qRT-PCR analysis was performed on a CFX96 Real-Time PCR system (Bio-Rad Laboratories, Hercules, CA, USA) using Eva Green SMA (Bio-Rad Laboratories). To evaluate relative gene expression levels, the SlEF1-α gene (Solyc06g005060), SlACT (Solyc03g078400), and SlUBI3 (Solyc01g056940) were used as the internal reference, and 35 pairs of gene-specific primers were used for the qRT-PCR (Table S1). The relative expression levels of these genes were calculated using the 2 − method (Pan et al., 2012). To ensure the statistical credibility of the results, all experiments were performed with three biological replicates and three technical replicates. And data were compared using t -test.

Comparative phylogenetic analysis of the C2H2-ZFs
To explore the phylogenetic relationships of the C2H2-ZFPs between tomato and the model plant Arabidopsis, a NJ phylogenetic tree was firstly constructed from an alignment of the 104 tomato C2H2-ZFPs and 97 Arabidopsis C2H2-ZFPs (Table S3). The sequences were clustered into six major groups (Fig. 1A, Group 1-6, Table S3), each of which could be further subdivided into different subgroups according to their bootstrap values. Furthermore, the tomato C2H2-ZFPs were tightly grouped with the Arabidopsis C2H2-ZFPs (Groups 1 to 4, and Group 6; Fig. 1A), except for the Group 5 ( Fig. 1A), indicating that we could assume the putative function of these genes in tomato based on the Arabidopsis C2H2-ZFPs in same group. Subsequently, we reconstructed the phylogenetic distribution of the 104 C2H2-ZF genes using different methods to clearly elucidate the relationships between the C2H2-ZF family genes in tomato. Results showed that the phylogenetic tree constructed by different methods displayed the differences, such as NJ tree (Fig. 1B), ML tree (Fig. S1A), UPGMA tree (Fig. S1B) and MP tree (Fig. S1C). For the NJ phylogenetic tree, 104 C2H2-ZFPs were classified into nine groups (I to IX; Fig. 1B). Among them, four genes in Group VII (Fig. 1B) were all grouped in Group 1 (Fig. 1A), some genes in Group VII, VIII and IX (Fig. 1B) was closely related to Group 1 and 2 (Fig. 1A), and Group II, III, IV ( Fig. 1B) was closely related to Group 3 (Fig. 1A), while a small number of C2H2-ZFPs were clustered into the different groups in tomato (Figs. 1A and 1B). These results suggested that the same clades of phylogenetic tree were likely to represent the closest homologous gene pairs between tomato and Arabidopsis, and C2H2-ZFs have also undergone sequence diversification independently in different organisms. In addition, 104 C2H2-ZFs were irregularly distributed between these groups in tomato (Fig. 1B), such as Groups II, VIII, and IX were the main clades, containing 18, 26, and 28 genes, respectively, while Groups I, IV, and VII were the smallest clades, containing three, three, and four tomato C2H2-ZFs, respectively (Fig. 1B).

Analysis of the exon-intron structures and conserved motifs in the tomato C2H2-ZFs
The Gene structural diversity within a gene family can be used as an evolutionary marker (Zhu et al., 2018). To gain further insights into the structural diversity of tomato C2H2-ZFs, , and the remaining C2H2-ZFs contained more than four introns (9.6%). In general, genes in the same group shared similar intron/exon arrangements in terms of intron numbers and exon length. For example, most C2H2-ZFs in Groups III, IV, VI, VII, VIII and IX genes had zero to one intron, and in Group II had two to three introns, which had the normal intron length (Fig. 3, Table S2). In contrast, the gene structure appeared to be more variable in groups I and V, which had striking distinctions in the exon/intron structure variants (Fig. 3, Table S2). In addition, we compared the exon-intron structure of each of the C2H2-ZFs in the same cluster of the different phylogenetic tree constructed by NJ (Fig. 3), ML (Fig. S1A), UPGMA (Fig. S1B) and MP (Fig. S1C), respectively. We found that genes in the same group had the highly similar intron/exon arrangements in the NJ phylogenetic tree (Fig. 3), indicating that the gene structure patterns were consistent with the NJ phylogenetic analysis. Using the MEME tool, a total of 10 conserved motifs were identified in the C2H2-ZFPs, and the lengths of these conserved motifs varied from 7 to 31 amino acids (Fig. 4,  Fig. S2). Among them, Motif 1 was widely detected in all C2H2-ZFPs, corresponding to the C-X2-C-X12-H-X3-H single ZF structure, which located at the N-terminal region of C2H2-ZFPs in groups II, and VI-IX (Fig. 4). Some groups also contained specific motifs; for example, Motifs 2 and 3 were present in the N-terminal region of Group II and the C-terminal region of many members in Groups III and IV; while Motif 4 was only detected in the N-terminal region of Group II, indicating that they may be relevant to the specific functions of these genes. The members of Groups I and V-IX have relatively simple motif patterns in comparison with Groups II to IV, implying the possible functional divergence of the C2H2-ZF genes in tomato. Taken together, the structure and motif conservation within the C2H2-ZF genes supports the results of the NJ phylogenetic analysis. Variations in the motif compositions between subfamilies might be explained by their functional diversification.

Chromosomal locations and gene duplication events in the C2H2-ZFs
To gain insight into the organization of these genes in the tomato genome, the 104 C2H2-ZFs were mapped onto their respective chromosomes, which acquired from tomato genome database (The Tomato Genome, 2012). The C2H2-ZF genes were unevenly distributed throughout the tomato genome and generally more abundant at the both ends of the chromosomes (Fig. 5, Table S2). Chromosome 6 contained the largest number of C2H2-ZFs (16), followed by chromosomes 1, 2, 3, 4, 5, 9, 10, and 11, each of which contained 7 Figure 5 Genomic distribution of the C2H2-ZFs across the tomato chromosomes. The chromosome numbers and sizes (Mb) are indicated at the top and right of each bar, respectively. Genes from the same subgroups are indicated by the same color, which is consistent with the coloration used on the phylogenetic tree (Fig. 1B). The C2H2-ZF gene pairs resulting from segmental duplication genes are connected by red lines, and the tandem duplication gene clusters are marked in black rectangles.
Full-size DOI: 10.7717/peerj.7929/ fig-5 to 12 C2H2-ZF s. Chromosomes 0 (random chromosome) and 12 contained two and one genes, respectively. In addition, the duplication events of C2H2-ZFs were also analyzed in tomato genome since gene replication play an important role in genomic expansions and realignments. We identified 15 pairs of tandem-duplicated gene pairs (with two or more homologous genes within 100 kb region) located on chromosomes 1, 2, 4, 5, 9, 10, and 11 (Fig. 5), respectively. The closely related clustered sequences of Groups VI, VIII, and IX are mainly located on chromosomes 1, 2, 5, 9, 10, and 11, suggesting that the expansion of this gene family may have occurred via localized or intra-chromosomal duplication. In addition to tandem duplications, seven segmental duplication events were detected to scatter in eight chromosomes (Fig. 5). Furthermore, many homologous genes were located in different chromosomes in tomato, supporting the high conservation of the C2H2-ZF gene family.

Functional annotation of C2H2-ZFs
All 104 C2H2-ZFs were subjected to GO enrichment for investigating their functional annotation. As a result, a total of 43 C2H2-ZFs were mapped on the GO database, resulting in 285 annotations (Table S5), which were distributed across three ontology categories (biological processes, cellular components, and molecular functions) with 30 function terms (Fig. S5). Furthermore, most tomato C2H2-ZFs were annotated as being associated with meal ion binding, DNA-binding transcription factor activity, nucleus and regulation of transcription, DNA-templated, respectively (Fig. S5).

Expression patterns of the C2H2-ZFs in various tissues and organs
Using the TomExpress database (available online: http://tomexpress.toulouse.inra.fr/), we investigated the expression levels of the 104 C2H2-ZFs in various tissues of the tomato cultivar Micro Tom, including its roots, leaves, flower buds, petals, flowers, fruits, flesh, and peel, which were visualized using a heatmap (Fig. 6). The C2H2-ZFs had different expression patterns across the various tissues. Firstly, the clear differences in expression between the genes of Group II, III and V in comparison with those of the other groups were consistent with their different gene structures and the phylogenetic tree analysis (Figs. 3 and 6). In addition, we found that a small few genes typically had relatively high expression levels across various tissues and organs at different development stages, such as Solyc01g099340.

Expression of the C2H2-ZFs under heat stress
To improve the reproducibility and reliability of the qRT-PCR analysis obtained in this study, three previously reported tomato internal reference genes, including SlEF1-α (Solyc06g005060), SlACT (Solyc03g078400), and SlUBI3 (Solyc01g056940), were primarily detected for the their quantification stability in the leaves, stems, and roots under the control and heat stress by qRT-PCR method. The results showed that SlEF1-α (Fig. S3A) displayed relatively greater stability than SlACT and SlUBI3 among the different tomato tissues (Figs. S3B and S3C, Table S4), which were used for further analysis in this study. Many of the C2H2-ZFs previously described in other crops were involved in responding to abiotic stresses, such as drought, heat, and salt stress (Muthamilarasan et al., 2014;Sakamoto et al., 2004;Sun et al., 2010;Wang et al., 2018). To confirm the potential roles of candidate tomato C2H2-ZFs in heat stress, the expression profiles of 34 C2H2-ZFs were finally detected in leaves, stems and roots of tomato under heat stress (42 • C), which might not be markedly induced by the day/night cycle, except the Solyc10g085560.2.1 (Fig. S4). Combined with the expression phylogenetic analysis, we found that genes showed the diversity expression patterns under heat stress (Figs. 7 and 8). Of them, the expression  et al., 2017). Genes from the same subgroups are indicated by the same color, which is consistent with the I-IX used on the phylogenetic tree (Fig. 1B). The textbox indicates the C2H2-ZF genes showed the similar expression patterns during the fruit development from Group IX. The color scale (0 to 10, dark blue to red) represents the standardized gene expression levels. Error bars represent the standard deviations from three biological replicates. The relative expression levels were normalized according to the reference gene (SlEF1-α; Solyc06g005060) to the values in control (0 h). Data were compared using Student's t -test: *, P < 0.05 and **, P < 0.01, respectively. R, S, and L indicate the roots, stems, and leaves, respectively. A-G, and H-P represents genes were classified into Group VIII, and IX, respectively. Full-size DOI: 10.7717/peerj.7929/ fig-8 levels of 18 genes analyzed from Group II to VII were found to differ in roots, stems and leaves, under heat stress (Figs. 7A-7S). Of these, Solyc02g062940.3.1 and Solyc02g068990.3.1 were sustained up-regulated in the roots, stems, and leaves during heat stress treatment (Figs. 7F and 7R), and Solyc02g068980.1.1 was significantly up-regulated in the roots and stems with the similar expression patterns (Fig. 7P), but Solyc08g006470.3.1 was only significantly up-regulated by the heat treatment in the roots (Fig. 7L). For the largest classification groups VIII and IX, the expression levels of seven and nine genes from Group VIII and IX, were also investigated (Fig. 8) (Fig. 8G). In Group IX, only Solyc01g005190.1.1 was significantly up-regulated in all tissues after heat treatment (Fig. 8M) Taken together, qRT-PCR was performed for 34 selected genes from different cluster groups under heat stress, and showed the various expression patterns in the roots, stems, or leaves. Among them, seven genes were strongly up-regulated in the roots, stems, and leaves, while one gene were down-regulated; and five genes up-regulated both in roots and stems, and five genes specially expressed in the roots, and so on (Figs. 7 and 8). Hence, these results suggest that these C2H2-ZF genes might be associated with the heat stress during the seedlings development in tomato.

DISCUSSION
The C2H2-ZFPs are known to play important roles in many biological processes (An et al., 2012;Joseph et al., 2014;Lyu & Cao, 2018;Wang et al., 2018;Weng et al., 2015). To date, C2H2-ZFs have been identified and characterized in a variety of plant species, including soybean (Yuan et al., 2018), tobacco (Yang et al., 2016, Arabidopsis (Englbrecht, Schoof & Bohm, 2004), rice (Agarwal et al., 2007, poplar (Liu et al., 2015), and petunia (Kubo et al., 1998). Despite these advances, little was previously known about these genes in tomato, a model system for both fleshy fruit development and the Solanaceae species in general (The Tomato Genome, 2012). In this study, using 97 Arabidopsis C2H2-ZFP sequences as a query, we identified 104 C2H2-ZF family members in the tomato genome, which contains at least one C2H2-ZF motif (X2-Cys-X(2-4)-Cys-X12-His-X(3-5)-His), and the lengths of these sequences varied from 96 to 1,178 amino acid residues, with striking distinctions (Table S2), suggesting that a high degree of complexity among the tomato C2H2-ZFs (Liu et al., 2015). The 'QALGGH' motif was almost invariant in the tomato C2H2-ZFPs (Fig. 2), however, the C2H2-ZFP subfamilies in other plant species have previously been defined based on changes to the conserved ''QALGGH '' motif (Fedotova et al., 2017;Liu et al., 2015;Razin et al., 2012;Takatsuji, 1999;Wei, Si & Yang, 2016;Yuan et al., 2018;Zhang et al., 2016). In this study, to reveal phylogenetic relationship of tomato C2H2 family members, 104 C2H2-ZFPs were divided into nine major groups according to the NJ phylogenetic tree (Fig.  1B), which were well consistent with arrangements, numbers, and types of their C2H2-ZF domains (Fig. 2). This suggests that the C2H2-ZFs were highly conserved during evolution and may have similar functions in tomato. However, classification of the C2H2-ZFs in NJ phylogenetic tree displayed the difference (Figs. 1A and 1B, Table S3), suggesting that they may show differences in gene function between the Arabidopsis and tomato.
The integration and rearrangement of gene fragments during evolution can lead to increases or decreases in the number of introns and exons present; therefore, the structural variation of genes is important for the evolution of gene families (Xu et al., 2012). Here, the gene structures and motifs present were highly similar among members of the same C2H2-ZF groups (Figs. 3 and 4); for example, the members of Groups I, II, and V had 3-5 exons (Fig. 3), while the most complex arrangements of motifs were observed in Group II (Fig. 4). These results were similar to those of previous analyses of the C2H2-ZF family genes in maize (Zea mays) (Wei, Si & Yang, 2016), soybean (Yuan et al., 2018, and poplar (Liu et al., 2015). Therefore, our results suggest that the sequences and biological functions of the C2H2-ZFPs were relatively conserved among members of the nine subgroups, indicating that our classification of the tomato C2H2-ZFPs was reasonable. About 62.5% had no introns and 27.9% had one to three introns with short length, which is consistent with the results that the genes with no intron or a short intron were tended to retain in plants (Li & Liu, 2019;Mattick & Gagen, 2001). Correspondingly, genes with fewer introns could be rapidly activated for respond to environmental challenges (Jeffares, Penkett & Bähler, 2008;Li & Liu, 2019), so C2H2-ZFs play an important roles in responding to abiotic stresses (Muthamilarasan et al., 2014;Sakamoto et al., 2004;Sun et al., 2010;Wang et al., 2018). In addition, previous results showed that C2H2-ZFPs with a plant-specific conserved domain 'QALGGH' play important roles in diverse environmental stress responses (Agarwal et al., 2007;Kam et al., 2008;Liu et al., 2015). In present study, about 48% (50 of 104) of C2H2-ZFPs from tomato had plant-specific conserved domain 'QALGGH', which was a larger number compared with other experimental models Arabidopsis (36%) and rice (34%), suggested that these C2H2-ZFPs are more important for tomato plants. Furthermore, most members in the same phylogenetic group had the similar intron/exon arrangements and motif compositions (Figs. 3 and 4). In addition, gene duplication events has been reported for C2H2-ZF gene families in different plants (Agarwal et al., 2007;Guo et al., 2008;Yuan et al., 2018), and which were also revealed the widely gene duplication events in the tomato genome, including 15 tandem duplication and 7 segmental duplication (Fig. 5). Thus, gene duplication events are one of the primary forces for the C2H2-ZFs gene evolution during the speciation and evolution of tomato. These results reflected the diverse functions of tomato C2H2-ZFs and will be helpful for their future functional analysis.
The tissue-specific expression of genes usually is preliminarily used to predict their corresponding functions (Xiao et al., 2019). Therefore, we assessed the expression profiles of the 104 C2H2-ZFs in various tomato tissues using published transcriptomic data (Zouine et al., 2017), revealing that the C2H2-ZF genes display a diversity of relative expression patterns in different organs (Fig. 6) and may therefore play differing roles in various tissues or biological processes. But the homologous genes had similar expression patterns, such as Solyc10g078970.1.1 (SlHair), AT1G68360 (GIS3), AT1G10480 (ZFP5), and AT1G67030 (ZFP6 ) were all found to be grouped into Group 1 (Fig. 1A), which were previously reported to play important roles in controlling trichome development (An et al., 2012;Chang et al., 2018;Sun et al., 2015;Zhou et al., 2013). Reported genes, AT5G04340 (ZAT6 ) and AT1G27730 (ZAT10/STZ ), Solyc06g075780.1.1 (SlZF3) and Solyc07g006880.1.1 (SlZFP2) were classified into the Group 2 (Fig. 1A) and Group IX (Fig. 1B), which showed the similar functions; for example, AT5G04340 (ZAT6 ) and AT1G27730 (ZAT10/STZ ) was involved into the organs development and the adversity stress responses (Devaiah, Nagarajan & Raghothama, 2007;Mittler et al., 2006), and Solyc06g075780.1.1 (SlZF3) enhanced the salt-stress tolerance in tomato (Li et al., 2018), and Solyc07g006880.1.1 (SlZFP2) was characterized as a repressor to fine-tune ABA biosynthesis during fruit development (Weng et al., 2015), and they showed the higher expression levels during the fruit ripening in tomato (Fig. 6), which will be helpful for dissecting their roles in fruit ripening. In addition, the C2H2-Type Zinc Finger Protein, SUPPRESSOR OF FRIGIDA4 (SUF4, AT1G30970.3) could bind to the Flowering Locus C (FLC) promoter region, and play a role in transcriptional activation of FLC (Kim et al., 2006). In this study, the homologous genes, Solyc02g032120.3.1 and Solyc02g081620.3.1 belong to group V (Fig. 1B), and showed the relative high expression in the flowers (Fig. 6). These results suggested that the members within each group might have similar functions between tomato and Arabidopsis.
In nature, heat stress is one of the critical environmental factors that adversely affects plant growth and delays development (Guan et al., 2013;Yang & Guo, 2014). Several C2H2-ZPs were also characterized and participated in the interaction of plants and stress, such as Zat6 (Devaiah, Nagarajan & Raghothama, 2007), ZAT10/STZ (Mittler et al., 2006), and C2H2 zinc-finger protein OsZFP213 (Zhang et al., 2018). To further characterize whether tomato C2H2-ZF genes play a role in heat-stress tolerance, the expression profiles of 34 C2H2-ZF genes randomly selected from all groups were analyzed in the roots, stems, and leaves of wild-type tomato under heat stress. As expected, the majority of the C2H2-ZFs were significantly up-regulated when the plants were exposed to heat treatment (42 • C), with different expression modes in the different tissues ( Figs. 7 and 8). In plants, roots are known to play important roles in resisting abiotic stress, sensing soil changes and sending a series of signals to reduce root damage and maintain plant growth under abiotic stress (Liu et al., 2015;Lynch, 1995). The heat treatment used in the present study specifically induced the expression of 15 C2H2-ZF genes in the roots (Figs. 7 and 8); for example, Solyc08g006470.3.1, Solyc10g084910.2.1, and Solyc09g011110.1.1 were strongly up-regulated in the roots at all time points, but not in the stem or leaves (Figs. 7L, 8C and 8D), indicating that they may play specific roles in the root responses to heat stress. Furthermore, Solyc02g062940.3.1, Solyc02g068990.3.1, and Solyc01g005190.1.1 were significantly induced in all three tissues during all time points (Figs. 7F, 7R, and 8M), while Solyc12g0883900.1.1 was significantly suppressed in the roots, stems, and leaves (Fig. 8F), suggesting these C2H2-ZFs might play important roles in mediating the response of tomato plants to heat stress. In addition, previous study showed that the Solyc06g075780.1.1 (SlZF3) could enhance salt-stress tolerance in tomato (Li et al., 2018), but we found that it was also induced by the heat treatment (Fig. 8I). These differences suggest that the tomato C2H2-ZFs may play a variety of roles in the response to heat stress, with the strongly suppressed genes potentially interacting synergistically with other genes involved in this process. Although the role of C2H2-ZF genes in these processes is not yet known, but the above-mentioned tomato C2H2-ZF genes with significant changes after heat treatment are useful in selecting candidate genes for functional validation in relation to heat stress in tomato.

CONCLUSIONS
In this study, we characterized 104 C2H2-ZFs in the tomato genome using a genome-wide analysis. Examination of their phylogenetic relationships, chromosomal locations, gene structures, conserved motifs, and expression profiles revealed high levels of similarity between the identified subgroups of this family. This study lays the foundation for elucidating the functions of these important genes in future studies. In addition, the expression profiles of the C2H2-ZFs were evaluated during a heat stress treatment. These findings provide insight into the mechanisms of the C2H2-ZF function during the response to heat stress in tomato and potentially other Solanaceae species. Further molecular and functional analyses of these genes could suggest a strategy to improve heat tolerance to tomato plants.


extfieldsofstudy: Medicine Biology

text:
Host Cell Death Responses to Non-typhoidal Salmonella Infection

Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) is a Gram-negative bacterium with a broad host range that causes non-typhoidal salmonellosis in humans. S. Typhimurium infects epithelial cells and macrophages in the small intestine where it replicates in a specialized intracellular niche called the Salmonella-containing vacuole (SCV) and promotes inflammation of the mucosa to induce typically self-limiting gastroenteritis. Virulence and spread of the bacterium is determined in part by the host individual's ability to limit the infection through innate immune responses at the gastrointestinal mucosa, including programmed cell death. S. Typhimurium however, has evolved a myriad of mechanisms to counteract or exploit host responses through the use of Type III Secretion Systems (T3SS), which allow the translocation of virulence (effector) proteins into the host cell for the benefit of optimal bacterial replication and dissemination. T3SS effectors have been found to interact with apoptotic, necroptotic, and pyroptotic cell death cascades, interfering with both efficient clearance of the bacteria and the recruitment of neutrophils or dendritic cells to the area of infection. The interplay of host inflammation, programmed cell death responses, and bacterial defenses in the context of non-typhoidal Salmonella (NTS) infection is a continuing area of interest within the field, and as such has been reviewed here.

In immunocompromised individuals, S. Typhimurium can cause invasive disease that requires antibiotic treatment or hospitalization. Murine infections with S. Typhimurium result in invasive disease and bacteremia, and thus are a more representative model of invasive salmonellosis but are nevertheless used to great effect to study the pathogenesis of S. Typhimurium in vivo.
The interactions between NTS and host cell processes during host invasion and the initial establishment of infection have been reviewed previously by LaRock et al. and as such are only briefly described here (5). Once ingested, S. Typhimurium enters the gastrointestinal tract and uses flagella to access the epithelial layer of the terminal ileum. Inflammatory responses in the epithelium release key nutrients required by the bacteria, also causing diarrheal symptoms that promote transmission (6,7). Following contact with the epithelium, S. Typhimurium utilizes a Type III Secretion System (T3SS) encoded on Salmonella pathogenicity island-1 (SPI-1) to translocate effector proteins (such as SopE2, SipA, and SopB) into the epithelial cell cytosol, inducing actin rearrangement, membrane ruffling, and non-phagocytic cellular uptake of the bacteria into the host cell ( Figure 1) (8)(9)(10). Inside the intracellular space, flagella are no longer required for motility of the bacteria, and are typically downregulated in order to avoid host immune responses (11)(12)(13)(14). Internalization of S. Typhimurium causes formation of an endosome termed the early Salmonella-containing vacuole (SCV). Here, a second T3SS (encoded by the SPI-2 locus) is used to translocate virulence proteins such as SifA, SopD2, and SseJ, acidifying the vacuole and maturing the SCV into the ideal replicative niche for the bacteria (15). The late stage SCV enables efficient bacterial replication, while interconnected networks of Salmonella-induced filaments (SIFs) allow enclosed bacteria to acquire nutrients (15,16). Other SPI-2 effectors prevent lysosomal fusion with the SCV, inhibiting recruitment of lysosomal enzymes and trafficking markers that would promote degradation of the vacuole (15,17). In epithelial cells, subpopulations of S. Typhimurium have been observed in the cytosol, resulting in bacterial hyperreplication and host cell extrusion (18). Host guanylate-binding Abbreviations: A/E, attaching and effacing; AIM2, absent in melanoma 2; AP-1, activator protein 1; ASC, apoptosis-associated speck-like CARD-containing protein; AvrA, avirulence gene A; CARD, caspase activation and recruitment domain; cIAP, cellular inhibitor of apoptosis; EHEC, enterohemorrhagic Escherichia coli, EPEC, enteropathogenic E. coli; FADD, Fas-associated protein with death domain; GBP, guanylate-binding protein; GSDMD, gasdermin D; IFN, interferon; IFNAR1, interferon alpha/beta receptor alpha chain; IL-1β, interleukin 1β; IKK, inhibitor of kappa kinase complex; JNK, c-Jun N-terminal kinase; LUBAC, linear ubiquitin chain assembly complex; MAPK, mitogen activated protein kinase; MLKL, mixed lineage kinase domain-like protein; MKK4, MAPK kinase 4; NF-κB, nuclear factor kappa B; NLR, Nod-like receptor; NLRC4, NLR family CARD domain-containing 4; NLRP3, NLR family pyrin domain-containing protein 3; PAMP, pathogen-associated molecular pattern; PipA, pathogenicity island-encoded protein A; PRR, pattern recognition receptor; RIPK, receptor interacting serine/threonine protein kinase; TAK1, transforming growth factor beta-activated kinase 1; TLR, Toll-like receptor; TNF, tumor necrosis factor;  TNFR1, TNF receptor 1; TRADD, TNFR1-associated death domain protein;  TRAF, TNFR associated factor; TRAIL, TNF-related apoptosis-inducing ligand; TRAIL-R1, TRAIL receptor 1; SIF, Salmonella induced filaments; SlrP, Salmonella leucine-rich repeat protein; SopB, Salmonella outer protein B; SpvB, Salmonella plasmid virulence gene B; SseL, Salmonella secreted effector L. proteins (GBPs), expressed following Type I or II interferon (IFN) signaling, can also lyse the SCV, exposing S. Typhimurium to the cytosol (19)(20)(21).
Cytosolic S. Typhimurium enable the detection of pathogen-associated molecular patterns (PAMPs), such as lipopolysaccharide (LPS) and flagellin, by pattern recognition receptors (PRRs) or Nod-like receptors (NLRs). PRRs act to recruit immune cells to infected tissues and limit bacterial virulence through the activation of pro-inflammatory signaling. The ability of Salmonella infection to induce tumor necrosis factor (TNF) production in epithelial cells and macrophages is well-documented (22)(23)(24). TNF signaling typically reinforces the production of pro-survival cytokines and anti-apoptotic factors via nuclear factor kappa B (NF-κB) or mitogen-activated protein kinase (MAPK) signaling cascades (25)(26)(27). However, effector proteins such as GtgA, SspH1, SptP, and potentially SseL can prevent the activation of these pathways, instead driving TNF signaling toward programmed cell death cascades (28-34). These include apoptosis, necroptosis, and pyroptosis, and are triggered by TNF and other death receptor ligands, or inflammasome activation (Figure 1). Death of the host cell allows escape of S. Typhimurium into the extracellular space, and uptake of the bacteria by professional phagocytes. Neutrophils play a key role in the overall clearance of S. Typhimurium, killing the phagocytosed bacteria through the activity of reactive oxygen species (ROS), while infected dendritic cells and macrophages can spread the bacteria to the mesenteric lymph nodes, spleen, and liver (12,(35)(36)(37).

APOPTOTIC CELL DEATH PATHWAYS DURING SALMONELLA INFECTION
Apoptosis is a caspase-dependent form of programmed cell death, induced in damaged or stressed cells in response to intrinsic or extrinsic signaling cascades (38). The apoptotic process results in DNA fragmentation, phosphatidylserine exposure, formation of apoptotic bodies, and the display of "eat me" signals to prompt phagocytic clearance of the dying cell. Intrinsic apoptosis is triggered by DNA damage, accumulation of ROS or endoplasmic reticulum (ER) stress, resulting in mitochondrial outer membrane permeabilization and activation of caspase-9. Caspase-9 catalyzes the activation of caspase-3 and caspase-7, which execute the biochemical and morphological changes characteristic of apoptosis (38). In contrast, extrinsic apoptosis responds to ligand or cytokine binding to transmembrane death receptors on the surface of the cell. Death receptors possess an apoptosis-activating death domain, and include receptors such as Fas, TNFR1, and TRAIL-R1. Upon TNF stimulation, TNFR1 recruits adaptor proteins such as TNFR1-associated death domain protein (TRADD), TNFR-associated factor 2 (TRAF2) and receptor-interacting serine/threonine-protein kinase 1 (RIPK1) (Figure 1). RIPK1 is subject to ubiquitylation and phosphorylation events that direct TNFR1 signaling toward pro-survival NF-κB activation (39). In the absence of modifications, RIPK1 associates with pro-caspase-8, TRADD and Fas-associated protein with death Frontiers in Immunology | www.frontiersin.org FIGURE 1 | membrane ruffling and actin rearrangement, resulting in non-phagocytic uptake of the bacteria. Alternatively, Salmonella uptake can occur due to M cell mediated transport across the epithelial barrier, or through sampling by phagocytic cells such as dendritic cells or macrophages. Once internalized, the SPI-1 T3SS and effectors are downregulated, while SPI-2 is upregulated to promote SCV formation and facilitate Salmonella replication. Throughout the infection, both SPI-1 and SPI-2 effector proteins interact with host innate immune pathways to either activate or inhibit inflammatory responses and programmed cell death. Signaling cascades have been simplified for clarity and are discussed in more detail in-text.
Alternatively, effectors such as SopB may have a role in preventing intrinsic apoptosis. SopB (also known as SigD) is a phosphoinositide phosphatase translocated by SPI-1 that has multiple reported virulence functions (8,52,53). Infection of mouse embryonic fibroblasts revealed that SopB is ubiquitylated by TRAF6, potentially as a mechanism of directing SopB activity within the host cell (54,55). SopB-TRAF6 interactions prevent the recruitment of TRAF6 to the mitochondria, inhibiting accumulation of ROS in the organelle, thus preventing intrinsic apoptosis (56). SopB phosphatase activity in epithelial cells also mediates the recruitment of Rho and Ras family GTPases to the site of infection, promoting pro-survival Akt signaling and inhibiting apoptotic responses downstream (57)(58)(59). Another SPI-1 translocated effector that alters apoptotic pathways is AvrA, which displays deubiquitinase and acetyltransferase activity. Studies of S. Typhimurium-infected HeLa or HCT116 cells demonstrated that AvrA deubiquitylates IκBα to suppress pro-survival NF-κB activation (60,61). Interestingly, in vivo mouse infections, as well as transfection of AvrA into HEK293T cells, indicated that AvrA also prevents apoptotic responses by acetylating MAPK kinase 4 (MKK4) and inhibiting the c-Jun N-terminal-kinase (JNK) pathway (62)(63)(64). Similarly, SpvC (a phosphothreonine lyase) acts to both dampen inflammation and suppress apoptosis by inactivating members of the MAPK pathway (65,66). While suppression of both pro-survival signaling and pro-apoptotic pathways may initially seem counterintuitive, it is likely that this duality allows Salmonella to prolong infection of epithelial cells, allowing greater opportunities for replication in this cell type.

SALMONELLA INFECTION AND NECROPTOTIC CELL DEATH
Necroptosis is a caspase-independent lytic form of programmed cell death that results in characteristic pore formation and the release of cellular contents and highly inflammatory damage-associated molecular patterns (DAMPs) into the extracellular space (67). Initially triggered by TNF binding to TNFR1, necroptosis occurs when caspase-8 is non-functional or inhibited. In the absence of active caspase-8, deubiquitylated RIPK1 is able to interact with RIPK3, subsequently forming an amyloid-like complex (called the necrosome), activating RIPK3 via autophosphorylation events (68). Active RIPK3 then mediates the phosphorylation of mixed lineage kinase domain-like protein (MLKL), enabling MLKL oligomerization and migration to the plasma membrane, triggering membrane permeabilization and lytic cell death (Figure 1) (68). Although RIPK3 and MLKL are critical for the induction of necroptosis, the precise mechanism by which active MLKL executes necroptosis remains unclear (38,69,70). Released DAMPs induce inflammatory responses in neighboring cells, promoting recruitment of innate immune cells and mediating tissue pathology in the immediate area (71).
Observations of necroptosis in response to S. Typhimurium infection have included studies comparing infected C57BL/6J wild type (WT) or type I IFN alpha/beta receptor 1 deficient (Ifnar1 −/− ) mice (72). Type I IFNs act through heterodimeric IFNAR1/IFNAR2 complexes to activate Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling cascades, resulting in the transcription of interferon-stimulated genes (ISGs) (73). Following intravenous S. Typhimurium infection, Ifnar1 −/− mice experienced improved survival compared to WT mice, while infected Ifnar1 −/− bone marrow derived macrophages (BMDMs) experienced reduced rates of cytotoxicity in vitro, with decreased activation of RIPK1 and RIPK3 (72). Immunoprecipitation of IFNAR1 in WT BMDMs indicated RIPK1 associates with IFNAR1 following Type I IFN stimulation, while in vivo infection of Ripk3 −/− mice induced similar cytotoxicity to Ifnar1 −/− mice (72). Robinson et al. thus proposed a role for Type I IFN signaling in inducing necroptosis in S. Typhimurium-infected macrophages (72). Later work found that signaling downstream of IFNAR1/RIPK1/RIPK3 interactions resulted in recruitment of phosphoglycerate mutase family member 5 (PGAM5) (74). PGAM5 recruitment by RIPK3 was suggested as a mechanism of promoting or executing necroptosis in S. Typhimurium-infected BMDMs via impaired production of antioxidants, resulting in ROS-mediated mitochondrial damage (74,75). However, studies outside the S. Typhimurium infection context did not support PGAM5 as a mediator of necroptosis, instead proposing that PGAM5 counteracts necroptosis by promoting autophagic degradation of mitochondria (inhibiting ROS production) (70,76,77).
Other explorations of necroptosis in the context of S. Typhimurium infection involved the use of qRT-PCR techniques to assess the expression of micro RNAs (miRNAs) induced by infection in RAW264.7 cells (78). A highly upregulated miRNA, miR-155, mediated cytotoxicity levels similar to S. Typhimurium-infected cells when transfected into RAW264.7s (78). Further in vitro transfections indicated that miR-155 induced RIPK1 and RIPK3 phosphorylation (indicative of necroptosis) by 18 h post-treatment, as well as cleavage of poly (ADP-ribose) polymerase-1 (PARP-1) in a similar manner to S. Typhimurium infection (78). Treatment with RIPK1 inhibitor necrostatin-1s partially rescued cell viability in miR-155 transfected cells, supporting a role for necroptosis in contributing to cytotoxicity (78). The authors suggested that PARP-1 activation occurs downstream of RIPK1/RIPK3 activation, however existing work in TNF-stimulated L929 cells instead proposes that PARP-1 contributes to a separate programmed necrosis pathway (78,79).
Virulence proteins may also play a role in mediating host necroptotic responses during S. Typhimurium infection. Salmonella secreted effector K1 (SseK1), SseK2, and SseK3 are a family of related virulence proteins with glycosyltransferase activity that share high sequence homology with the Arg-GlcNAc transferase, NleB, found in attaching and effacing (A/E) pathogens (80)(81)(82). SseK effectors reportedly inhibit TNFinduced NF-κB signaling and cell death in macrophages, through arginine glycosylation of FADD and TRADD by SseK1 and SseK3, respectively (83). In vitro infections of RAW264.7 cells with ∆sseK123 S. Typhimurium showed similar levels of caspase-3/-7 activation when compared to WT infection, but resulted in higher levels of MLKL phosphorylation, indicating that SseK1 and SseK3 may specifically inhibit necroptotic cell death (83). Reports of SseK binding targets remain inconclusive, with suggested glycosylation targets for SseK1 including GAPDH, FADD, and TRADD, while SseK2 may glycosylate FADD (83)(84)(85). Recently, mass spectrometry-based screens have identified TNFR1 and TRAIL-R as novel glycosylation targets of SseK3, and demonstrated that TRADD is the preferred binding target of SseK1 (85). Although the specific actions of SseK effectors have yet to be confirmed, collectively these results suggest that SseK1 and SseK3 modify TNFR superfamily members as well as TRADD or FADD, thus inhibiting both TNF-mediated NF-κB signaling and cell death via apoptosis or necroptosis.

INFLAMMASOME ACTIVATION AND PYROPTOTIC CELL DEATH DURING SALMONELLA INFECTION
Pyroptosis is a highly inflammatory, caspase-dependent form of lytic cell death characterized by pore formation and release of active IL-1β and IL-18 (86). Originally thought to be a caspase-1 dependent form of apoptosis or necrosis, pyroptosis is an important host defense mechanism against S. Typhimurium (87)(88)(89). Typically, pyroptosis in S. Typhimurium-infected cells is triggered by the sensing of flagellin (FliC and FljB) or PrgJ (a SPI-1 rod protein) by NLR family apoptosis inhibitory proteins (NAIPs), which then interact with NLR family caspase activation and recruitment domain (CARD)-containing protein 4 (NLRC4) to trigger assembly of a multiprotein complex called the NLRC4 inflammasome (90)(91)(92). NLRC4 recruits pro-caspase-1 via shared CARD domains, and can also recruit apoptosis-associated specklike protein containing a CARD domain (ASC), to assemble the inflammasome and induce the proteolytic activation of caspase-1 (Figure 1) (92). Active caspase-1 mediates pyroptosis by cleaving gasdermin-D (GSDMD), producing an N-terminal segment that forms multimeric pores in the cell membrane and releases cellular contents into the extracellular space (93,94). Caspase-1 also cleaves IL-1β and IL-18 into their active forms, allowing their release through the GSDMD-N pores, or following the process of necrosis or others [as reviewed by Eder et al. (95)] (93,(95)(96)(97)(98).
Crosstalk with caspase-8 and apoptotic pathways can also promote inflammasome activation in S. Typhimurium-infected cells. Studies of NLRP3 and NLRC4 interactions during S. Typhimurium infection detected IL-1β maturation mediated by ASC-caspase-8 specks, suggesting a role for caspase-8 as an inflammasome effector (105,117). Other studies have proposed roles for caspase-8 in priming inflammasome activation, or coordinating cleavage of caspase-1 in the absence of NLRP3 or NLRC4 (118).
Although not yet demonstrated, effectors such as SlrP, which induce downstream ROS accumulation, could contribute to inflammasome activation and pyroptotic responses due to NLRP3 detection of ROS. However, a study of IL-1β release in a murine S. Typhimurium in vivo infection context found that SlrP signaling inhibited IL-1β activation, contradicting this idea (119). Aside from SlrP, effectors such as SipB, SopE, or SopB may influence pyroptosis in S. Typhimurium-infected macrophage. Following secretion, SipB interacts with SipC to form a translocon pore, facilitating SPI-1 effector translocation into the host cell (120). SipB is reportedly sufficient to induce caspase-1-mediated "apoptosis" and IL-18 maturation in SipB transfected or S. Typhimurium-infected dendritic cells and peritoneal macrophages, potentially via direct interactions with caspase-1 (121)(122)(123). These results likely indicate pyroptosis, however the mechanisms by which SipB interact with caspase-1 or the inflammasome remain unclear.
S. Typhimurium SPI-1 effector SopE is a guanine nucleotide exchange factor that catalyzes the activation of host cell Rho GTPases such as Cdc42 and Rac1 (124). Activation of Rac1 by SopE has been reported to induce caspase-1 activation and IL-1β secretion during S. Typhimurium infection of HeLa or RAW264.7 cells, and in vivo infection of murine enterocytes (125). SopE-induced caspase-1 activation in macrophages was not due to NLRC4 sensing of flagellin, suggesting an alternative sensor mechanism (126). Other Gram-negative bacteria possess effectors that modify Rho GTPase activity, for instance Yersinia spp. effector YopT, which inhibits the activity of RhoA (102,127). This RhoA inactivation allows assembly of the pyrin inflammasome, resulting in downstream caspase-1 activity and pyroptosis in infected cells (102). This suggests interesting avenues of research for SopE-induced caspase-1 activation; however, pyrin activation has not been observed in response to changes in Rac1 or Cdc42 activity (127). In contrast to SopE, SPI-1 effector SopB plays a role in dampening inflammasome activation. SopB has been associated with the downregulation of NLRC4 in S. Typhimurium-infected macrophages and B cells (128)(129)(130). NLRC4 depletion was associated with reductions in both IL-1β maturation and cytotoxicity in S. Typhimuriuminfected B cells, and was determined to be the result of Akt/YAP pathway activation (128,130). Loss of NLRC4 inhibits the dominant inflammasome involved in the pyroptotic response to S. Typhimurium infection, thus allowing the bacteria better opportunities for replication before escaping the host cell.
Lastly, although S. Typhimurium effectors both activate and inhibit inflammasome activation, current understandings of these effectors suggest that their translocation is under temporal and spatial control by the bacteria due to their translocating T3SS type. A recent study demonstrated that mutation of the SPI-1 T3SS resulted in decreased HMDM cytotoxicity and IL-1β release, while infection with ∆SPI-2 S. Typhimurium induced rapid cell death and IL-1β production in these cells (131). SPI-2 mutation also resulted in increased expression of SPI-1 effectors detectable by NLRC4 (FljB, PrgI, and PrgJ), suggesting that SPI-2 activity helps suppress the translocation of SPI-1 effectors later in infection (131).

CONCLUDING REMARKS
Investigating cell death in the context of S. Typhimurium infection has revealed highly complex interactions between host signaling cascades and bacterial virulence effectors. Tightly regulated control of T3SS effector translocation supports bacterial requirements at different infection stages, allowing S. Typhimurium to evade or promote cell death responses. Our understanding of Salmonella-host interactions is continually evolving, with virulence mechanisms and effector proteins still to be characterized and improved in vitro and in vivo models for testing hypotheses frequently emerging. While the current literature does not describe immediate applications for exploiting programmed cell death in treatment of salmonellosis, further exploration of NTS virulence factors could help characterize clinical isolates, leading to personalized therapies and improved patient outcomes. Additionally, the high specificity of Salmonella effector proteins could prove crucial to the development of novel genome or proteome editing tools (such as the recently described use of effectors from Shigella flexneri) (132). Overall, exploration of pathogen-mediated cell death provides crucial insights into how bacteria can mediate survival and dissemination between host cells and can further improve our general understanding of the importance of cell death in counteracting bacterial pathogenesis.

AUTHOR CONTRIBUTIONS
MW wrote the initial manuscript and designed the figure. JP and MW edited and revised the manuscript. Both authors read and approved the final manuscript.


s2fieldsofstudy: Biology Psychology

text:
DA-JC1 improves learning and memory by antagonizing Aβ31–35-induced circadian rhythm disorder

Studies have shown that a normal circadian rhythm is crucial to learning and memory. Circadian rhythm disturbances that occur at early stages of Alzheimer’s disease (AD) aggravate the progression of the disease and further reduce learning and memory in AD patients. The novel, dual GLP-1R/GIPR agonist DA-JC1 has been found to exert a stronger hypoglycemic effect than a GLP-1R agonist alone and has been shown to exert neuroprotective effects. However, it is not clear whether DA-JC1 improves the Aβ31–35-induced decline in learning and memory ability by restoring disrupted circadian rhythms. In the present study, we carried out a mouse wheel-running experiment and Morris water maze test (MWM) and found that DA-JC1 could effectively improve the decline of learning and memory and circadian rhythm disorders induced by Aβ31–35. After downregulating Per2 expression via lentivirus-shPer2 in the hippocampus and the hippocampal HT22 cells, we found that circadian rhythm disorders occurred, and that DA-JC1 could not improve the impaired learning and memory. These results suggest that DA-JC1 improves damage to learning and memory by antagonizing circadian rhythm disorders induced by Aβ31–35. The outcome of this ongoing study may provide a novel therapeutic intervention for AD in the future. Electronic supplementary material The online version of this article (10.1186/s13041-019-0432-9) contains supplementary material, which is available to authorized users.

Introduction
According to the World Alzheimer Report 2018, around 50 million people have dementia, and the number is projected to reach 152 million by 2050, of which 50-75% are Alzheimer's disease (AD) patients. Learning and memory dysfunction in AD patients seriously affect their quality of life [1]. Studies have shown that, as the main pathological change of AD, the deposition of amyloid-β protein (Aβ) in the brain damages learning ability and memory capacity [2]. However, the underlying mechanism is not yet understood.
Studies have shown that normal circadian rhythm is crucial to learning and memory [3]. Circadian rhythm disturbances that occur at early stages of AD aggravate the progression of the disease and further reduce learning and memory ability in AD patients [4,5]. Circadian rhythm disorders in AD patients manifest as excessive daytime sleepiness and fragmented sleep [6]. The circadian rhythms are daily oscillations in various biological processes that are regulated by a transcriptiontranslation feedback loop (TTFL) composed of circadian clock genes and proteins [7]. Studies have shown that abnormal deposition of Aβ is an important factor for the AD-related disruption of the circadian rhythm [8]. The 5xFAD mouse with high Aβ deposition was found to exhibit abnormal expression of the clock gene Per2 [9]. Our previous results also showed that hippocampal injection of Aβ31-35 caused circadian rhythm disorder in mice and abnormal expression of Per1 and Per2 [10]. So, can we improve the Aβ31-35-induced decline of learning ability and memory capacity by restoring disrupted circadian rhythms?
Studies have shown that AD has many similar pathophysiological characteristics with type 2 diabetes mellitus (T2DM). The insulin signaling pathways are impaired in both T2DM and AD patients [11]. Patients with T2DM have greater impairments in cognitive function [12], and patients with AD are at high risk of developing T2DM [13]. Hence, the T2DM drugs glucagon-like peptide 1 (GLP-1) and glucose-dependent insulin-promoting peptide (GIP) may be used to treat AD. It has been found that the novel, dual GLP-1R/GIPR agonist DA-JC1 has a stronger hypoglycemic effect [14] than GLP-1R agonist Liraglutide. DA-JC1 was found to play a neuroprotective role in Parkinson's disease mice by reducing synapse loss and motor dysfunction [15], with a longer half-life than a single-receptor agonist [16]. However, it is not clear whether DA-JC1 improves the circadian rhythm disorder and further restores the learning and memory impairment induced by Aβ31- 35. This study aimed to investigate whether DA-JC1 could effectively alleviate the circadian rhythm disorder and impairment of learning and memory induced by Aβ31-35 using the running-wheel and Morris water maze tests. Furthermore, the expression of Per2 was downregulated with lentivirus to explore whether the circadian rhythm was involved in DA-JC1's improvement of the decline in learning ability and memory capacity induced by Aβ31-35.

Experimental animals
Six-to-eight-week-old male C57BL/6 mice (18-22 g) were provided by the Experimental Animal Center of Shanxi Medical University. The mice were kept at room temperature, relative humidity levels of 35-55%, and free diet. The use of animals in experiments was in accordance with the national experimental animal use regulations.

Intrahippocampal injection
C57BL/6 mice were anaesthetized with 5% chloral hydrate by intraperitoneal injection. Animal heads were immobilized in a standard stereotaxic instrument according to the anatomical map of the mice, and reagents were injected into the CA1 area of the hippocampus (2.0 mm posterior to bregma, 1.8 mm lateral to midline, and 1.8 mm below the horizontal skull surface) at a uniform speed (0.2 μl/min).
In the Aβ31-35 group, Aβ31-35 was dissolved in tri-distilled water and diluted to 1 μg/μl, and then incubated for 36 h at a constant temperature of 37°C (water bath). A 7.5 nmol dose of Aβ31-35 was injected into the hippocampus of each mouse [17]. For the control group, the same volume of normal saline was injected. The DA-JC1 pre-administration group received intraperitoneal injections of 50 nmol/kg DA-JC1 for 1 week before intrahippocampal injection of Aβ31-35. The mice in the DA-JC1 group were only administered with an equivalent dose of DA-JC1 intraperitoneally for 1 week [18].

Morris water maze test
One week after hippocampal injection, the Morris water maze (MWM) test was used to study spatial learning and memory [19]. The water maze is a circular pool with a diameter of 120 cm and a depth of 30 cm. The inside of the water maze is painted black, and the water temperature is 23 ± 2°C. The pool was divided into four quadrants-northeast (NE), southeast (SE), southwest (SW), and northwest (NW)-and a round escape platform 6 cm in diameter and 24 cm in height was placed in the NW quadrant 1 cm below the water surface. A camera was fixed above the pool and captured the process of mouse swimming. The data were analyzed using Smart 3.0 image software. The MWM test consisted of two types: a place navigation trial and a spatial probe trial. In the place navigation trial, the mouse was placed into the water facing the maze's wall from a random quadrant; we monitored the animal until it reached the hidden escape platform and recorded the time this took as escape latency. If the animal failed to find the platform in the 1-min period, we placed it back on the platform and allowed it to remain on the platform for 10 s, then removed the animal and put it back in the cage. Mice were trained four times a day at 20-min intervals for five consecutive days. We then conducted probe trials similar to the hidden platform training, with the exception that no platform was in the maze on the sixth day. During testing, the mouse was released from a fixed point and had 60 s to swim in the maze. We tracked the percentage of time the animal spent in each quadrant of the maze.

HT22 cell culture
An HT22 mouse hippocampal neuronal cell line was purchased from GuangZhou Jennio Biotech Co., Ltd. The HT22 cells were cultured in DMEM complete medium with 10% fetal bovine serum and placed in a stable-temperature incubator at 37°C, 5% CO 2 , and saturated humidity. The cell synchronization was performed when the cells were completely attached. Complete medium was changed to the starvation medium with 1% fetal bovine serum. After 1 h culture, the circadian rhythm of HT22 cells was regarded synchronized as Circadian Time 0 (CT0). Then the starvation medium was changed to the complete medium, and the synchronized cells were cultured for n hours as CTn [20]. The cells of the control group were cultured in complete medium; the cells of the Aβ31-35 group were cultured in complete medium with 5 μM Aβ31-35; in DA-JC1 + Aβ group, the cells were pretreated with 300 nM DA-JC1 for 1 h, and then 5 μM Aβ31-35 was added; the cells of the DA-JC1 group were cultured in complete medium with 300 nM DA-JC1. Subsequently, the cells were collected at CT4, CT8, CT12, CT16, CT20, and CT24 to detect the expression of the circadian clock genes Per1 and Per2 and learning and memoryassociated proteins synaptophysin (SYP) and growthassociated protein 43 (GAP-43).

Western blot
We collected the cells by centrifugation and performed the lysis with RIPA lysate on ice, and the supernatant liquid was obtained after being centrifuged. We quantified the protein content using a BCA Protein Assay Kit and calculated the sample protein concentrations; then the protein was denatured for 10 min at 100°C. Samples were added to SDS-PAGE, and proteins were then transferred to PVDF membranes after electrophoresis. The membrane was blocked for 2 h at room temperature with 5% skimmed milk, then incubated with anti-SYP primary antibody (Santa Cruz, sc-17,750), anti-GAP43 primary antibody (Santa Cruz, sc-17,790), anti-PER1 primary antibody (Abcam, ab3443), and anti-PER2 primary antibody(Santa Cruz, sc-25,363) overnight at 4°C. Subsequently, the membrane was incubated with the corresponding secondary antibody for 2 h at room temperature after TBST washing. The Super ECL Plus ultrasensitive luminescent solution was added, and the image was captured using a gel imaging system. ImageJ was used to analyze the gray value and calculate the relative expression of the corresponding protein.
Wheel-running behavioral test C57BL/6 mice were randomly divided into four groups: control group, Aβ31-35 group, DA-JC1 + Aβ group, and DA-JC1 group. The mice of each group were placed in wheel-running device at 22 ± 2°C and a relative humidity of 35-55%. The animals were exposed to light/dark cycles of 12:12 h (LD) for 1 week, then transferred to constant darkness (DD) for 2 weeks. The endogenous circadian rhythm of mice was represented by circadian time (CT) in the DD condition. The circadian day was divided into 24 equal parts, with each circadian hour representing one CT and the onset of activity defined as CT12 [10]. Running wheel activity was recorded using the VitalView program and analyzed using ActiView software. The free running period and daily activity were the main indicators. After the end of the wheel running, the mice were decapitated at CT4, CT8, CT12, CT16, CT20, and CT24, and then the hippocampus was removed quickly and placed on ice in a dark environment to further detect the expression of Per1 and Per2.

Real-time PCR
The Per1 and Per2 mRNA expression levels were detected by real-time PCR at different CT time points. Specifically, the total RNA of HT22 cells was extracted using TRIzol and inverted to cDNA. The SYBR Green kit was used, and the corresponding primers were added to specific amplification. Primers were designed as follows: Per1 (Gen-Bank ID NM_001159367.1) forward: 5′-CAGCCGTGCTGCCTACTCATT-3′, reverse: forward: 5′-AAATGGTGAAGGTC GGTGTGAAC-3′, reverse: 5′-CAACAATCTCCACT TTGCCACTG-3′. All gene expression data from each sample were normalized with the expression of GAPDH at CT4 in the control group, and relative mRNA quantification was performed using the 2 -ΔΔCt method.

Detection of Per2 expression and efficiency in mice hippocampus after lentivirus interference
Hanbio Biotechnology Co., Ltd. provided the lentivirus vector construction (LV-shPer2-GFP-PURO, hereinafter abbreviated as LV-shPer2) with GFP-and puromycinresistant genes. Intrahippocampal injection of LV-shPer2 was used to interfere with Per2 expression in the mouse hippocampus. Mice were anesthetized and fixed in a standard stereotaxic instrument. The LV-shPer2 (1 μl virus per side, 0.2 μl/min) or the LV-NC (nonspecific shRNA lentivirus) was injected slowly into the bilateral hippocampus in the corresponding experimental group [21]. Hippocampal tissues were cut into 30 μm sections, and the slides were observed to confirm the efficiency of infection under a laser scanning confocal microscope. Then, the interference efficiency of Per2 was determined using Western blot. In addition, the mice of each group were subjected to a run-wheel behavioral test and Morris water maze test to detect circadian activity rhythms and learning and memory capacity, respectively.

Per2 gene silencing and efficiency detection in HT22 cells
Lentivirus LV-shPer2 was used to infect mouse hippocampal HT22 neurons to silence Per2 gene expression. In order to choose a more appropriate amount of virus, we first determined the optimal multiplicity of infection (MOI, the number of virions per cell in a transduction). The optimal MOI corresponds to the number of efficient lentiviral vectors needed per cell in order to obtain the maximal percentage of transduced cells. Suitable lentivirus and auxiliary agent polybrene were added to cells according to MOI. Virus-containing medium was replaced with fresh complete medium at 12-16 h after virus infection. Then the cells were screened after 72 h infection. Uninfected and virus-infected cells with uniform cell density were prepared for the pre-screening, and cells were cultured in complete medium containing puromycin. The culture medium was replaced every other day until all uninfected cells died. Then the virus-infected cells were cultured for 1-2 days in medium containing a 50% concentration of puromycin, the percentage of GFP-positive cells was observed under a laser scanning confocal microscope, and the interference efficiency was assessed by immunofluorescence and Western blot. The expression of Per1, and Per2 and the expression levels of learning and memory-related proteins SYP and GAP-43 were investigated in the LV-shPer2 group as well as the LV-NC group.

Statistical analysis
Statistical analysis was performed with SPSS 16.0 statistical software. The normal distribution of measured data was expressed as mean ± SEM. ActiView Biological Rhythm Analysis was used to analyze data from the wheel-running assay. JTK_CYCLE was used to detect the rhythmic expression of clock genes [22]. One-way analysis of variance (ANOVA) was used for multiple group comparisons, and a least significant difference (LSD) t test was used for comparison between groups. The significance level of α = 0.05, P < 0.05 was considered statistically significant.

Results
DA-JC1 improved the impairment of learning and memory capacity in C57BL/6 mice induced by Aβ31-35 To explore the effect of hippocampal injection of Aβ31-35 on the learning and memory capacities of mice, we used the Morris water maze test to observe the mouse swimming path, escape latency, percentage of time spent in the target quadrant, and percentage of distance traveled in the target quadrant. As shown in Fig. 1a, the escape latency gradually decreased in all groups after 5 days of acquisition training in the water maze. Compared with the control group, the escape latency of mice injected with Aβ31-35 in the hippocampus was significantly prolonged, indicating that Aβ31-35 could induce the decline of spatial learning ability in the hidden platform test. We also found that intrahippocampal injection of Aβ31-35 decreased the percentage of time and swim distance spent in the target quadrant, demonstrating that Aβ31-35 could induce spatial memory deficits (Fig. 1b). In addition, the escape latency was significantly shorter than that of the Aβ31-35 group after pretreatment with intraperitoneal injection of DA-JC1 (Fig. 1a). The percentage of distance traveled in the target quadrant and the time spent in the target quadrant were significantly prolonged (Fig. 1b), suggesting that DA-JC1 could effectively prevent Aβ31-35-induced attenuation of spatial learning and memory capacity in C57BL/6 mice.
DA-JC1 reversed the Aβ31-35-induced decline in the expression of SYP and GAP-43 in HT22 hippocampal neuronal cells SYP, a major synaptic vesicle protein, is an indicator of changes in synaptic plasticity [23]. GAP-43, a neuralspecific protein, plays a significant role in synaptic remodeling, which forms the basis of learning and memory [24]. In the present study, Western blot was used to detect the protein expression of SYP and GAP-43 in HT22 cells, and the data showed that Aβ31-35 could decrease SYP and GAP-43 protein expression compared with the control group. Pretreatment with DA-JC1 significantly reversed the decline in the expression of SYP and GAP-43, and there was no significant change in the DA-JC1 group (Fig. 2). These results showed that DA-JC1 upregulated the decreased expression of learning-and memory-related proteins such as SYP and GAP-43 induced by Aβ31-35 in HT22 cells.
DA-JC1 antagonized the Aβ31-35-induced a change in the circadian rhythm of C57BL/6 mice Wheel-running experiments were performed to explore the effect of Aβ31-35 on the endogenous circadian rhythm of C57BL/6 mice, and the results showed that mice in the control group displayed rhythmic running wheel activity under a DD environment. The movement phase and the resting phase were clearly demarcated, and the activities mainly occurred during subjective nights. Intrahippocampal injection of Aβ31-35 induced a change in the circadian rhythm, as shown by an unclear movement phase and resting phase (Fig. 3a, c) and a prolonged free running period compared with the control group (Fig. 3b). After intraperitoneal injection of DA-JC1, the movement/rest phases became more obvious, and activities were mainly concentrated in the subjective night (Fig. 3a, c), suggesting that DA-JC1 pretreatment partially restored the circadian rhythm disorder in mice. Compared with the Aβ31-35 group, the free running period was shortened (Fig. 3b). Taken together, these results showed that DA-JC1 pretreatment could antagonize Aβ31-35-induced circadian rhythm disorder in C57BL/6 mice.
DA-JC1 partially reversed the abnormal expression of Per1 and Per2 in the hippocampus induced by Aβ31-35 The expression of Per1 and Per2 genes in HT22 cells was detected by real-time PCR. JTK_CYCLE was used to detect rhythmic mRNA expression of Per1 and Per2. The results showed that Per1 mRNA expression did not have a circadian rhythm (Additional file 1: Figure S1), while Per2 mRNA expression had a circadian rhythm (Fig. 4a). The Per1 mRNA level was significantly decreased at CT12, and the Per2 mRNA level was significantly decreased at CT16 after exposure to 5 μM Aβ31-35. The mRNA levels of Per1 at CT12 and Per2 at CT16 showed an obvious increase after pretreatment with DA-JC1 for 1 h compared with the Aβ31-35 group. There was no significant difference in the levels of Per1 and Per2 mRNA expression between the DA-JC1 alone group and control group (Additional file 1: Figure S1a,  Fig. 4a). Then we further examined the expression of PER1 protein at CT12 and Per2 protein at CT16. The data showed that the expression of PER1 and PER2 proteins was significantly lower in the Aβ31-35 group, while pretreatment with DA-JC1 could restore the decline of PER1 and PER2 proteins. Similarly, DA-JC1 alone had no significant effect on the relative expression of PER1 and PER2 proteins (Additional file 1: Figure  S1b, Fig. 4b).
Furthermore, in order to prove that the hippocampal clock was involved in the disruption by Aβ31-35 and improvement by DA-JC1, the mRNA expression of Per2 in the hippocampal tissue was detected. The results showed that Per2 mRNA expression exhibited circadian rhythms at different time points in the control group, showing a trough at CT10 and a peak at CT16. The expression of Per2 mRNA was remarkably decreased by Aβ31-35 and recovered after pretreatment with DA-JC1 for 1 week compared with the Aβ31-35 group at CT16 (Fig. 4c). These results suggested that DA-JC1 could significantly ameliorate the abnormal protein expression of Per1 and Per2 induced by Aβ31-35 in the hippocampus.

Interference with Per2 by lentivirus caused the circadian rhythm disorder in mice
Lentiviral vectors expressing shRNA were used to suppress Per2 gene expression in mouse hippocampal tissue after intrahippocampal injection, and then voluntary wheel running was used to assess mouse circadian rhythms. Mice were randomly divided into the control group, negative control virus (LV-NC) group, and virus (LV-shPer2) group. Hippocampal tissue sections of each group were taken and observed under a laser confocal microscope. The GFP-positive cells were observed in the LV-shPer2 group (Fig. 5a) and LV-NC group (Fig. 5a). Then Western blot was used to detect the knockdown efficiency of the Per2 gene, and the results showed that, compared with the control group, Per2 expression in the hippocampus of LV-NC mice did not change significantly, whereas LV-shPer2 significantly decreased Per2 protein expression (Fig. 5b), indicating that shPer2 lentivirus transfection effectively reduced Per2 expression.
Furthermore, a voluntary wheel running behavioral test was used to measure circadian activity rhythms in Per2-deficient mice. The results showed that the suppression of mouse Per2 expression in the hippocampus caused a change in the running activity rhythm, which was manifested as movement fragmentation and abnormal moving and resting phases (Fig. 5c). Statistics showed that the free-running period increased (Fig. 5c) and the locomotor activity was irregular compared to the control group (Fig. 5d), indicating that circadian rhythm disorder had occurred in mice after interference in the Per2 gene.
The Per2 shRNA lentivirus weakened the expression of Per1 in HT22 cells HT22 cells were infected with LV-shPer2 to interfere with the expression of Per2. We first determined the optimal multiplicity of infection (MOI), and the results showed that the fluorescence intensity at an MOI of 60 was higher than that at 20 MOI (Fig. 6a). Then we used Western blot to detect Per2 protein at MOI 60. The protein expression of Per2 in HT22 cells infected with LV-shPer2 was reduced remarkably (Fig. 6b), suggesting that LV-shPer2 could suppress the protein expression of Per2 effectively. Further, real-time PCR was used to

Interference with Per2 by lentivirus caused decreased learning and memory abilities in mice
To investigate the effect of circadian rhythm disorder on learning and memory capacities, a Morris water maze test was performed after Per2 expression was suppressed by lentivirus-mediated RNA interference in mice. The results showed that the escape latency in Per2-deficient mice was significantly longer than that in the control group (Fig. 7a), and the percentage of time spent in the target quadrant and the percentage of distance traveled in the target quadrant decreased significantly compared with the control group (Fig. 7b). Furthermore, the protein expression of SYP and GAP-43, which can reflect learning and memory capacities, were detected in HT22 cells infected with LV-shPer2. The results showed that the expression of SYP and GAP-43 was significantly decreased after suppression of Per2 expression (Fig. 7c).
Taken together, these results suggested that silencing of Per2 expression in the hippocampus of mice caused decreased learning and memory capacity and declined expression of learning and memory-related proteins SYP and GAP-43.

DA-JC1 could not improve the abnormal learning and memory capacity induced by Aβ31-35 after silencing of Per2 expression in the hippocampus of mice
To explore the role of circadian rhythm in DA-JC1's improvement of the Aβ31-35-induced decline in learning and memory capacity of mice, LV-shPer2 was used to suppress the protein expression of Per2 and further disrupt the circadian rhythm. Mice were randomly divided into four groups: the control group, the shPer2 + Aβ31-35 group, the shPer2 + DA-JC1 group, and the shPer2 + DA-JC1 + Aβ31-35 group. The escape latency of the shPer2 + DA-JC1 group and the shPer2 + Aβ31-35 group was prolonged (Fig. 8a), and the percentage of time spent in the target quadrant and the percentage of distance traveled in the target quadrant were reduced significantly compared with the control group (Fig. 8b). However, there was no obvious difference in escape latency, the percentage of time spent in the target  (Fig. 8a, b), indicating that DA-JC1 could not improve the Aβ31-35-induced decline in learning and memory in mice after interference with Per2 by lentivirus.
Similarly, the protein expression levels of SYP and GAP-43 were significantly lower in the shPer2 + DA-JC1 group and shPer2 + Aβ31-35 group than in the control group, and there was no significant difference between the shPer2 + DA-JC1 + Aβ31-35 group and shPer2 + Aβ31-35 group (Fig. 8c), suggesting that Per2 gene silencing resulted in the inability of DA-JC1 to improve the decreased expression of SYP and GAP-43 protein in HT22 cells induced by Aβ31-35.

Discussion
In the present study, the results of mouse wheel running and the Morris water maze test showed that the new, dual GLP-1 and GIP receptor agonist DA-JC1 could improve the reduced learning and memory capacity of mice and circadian rhythm disorder induced by Aβ31-35. After downregulating Per2 expression via lentivirusmediated knockdown of the Per2 gene in the hippocampus and the hippocampal HT22 cells, we found that DA-JC1 could not improve the learning and memory impairment induced by Aβ31-35 in mice. Therefore, we believe that DA-JC1 mitigated Aβ31-35-induced learning and memory impairment by improving circadian rhythm disorder.
Studies have shown that AD patients experience progressive learning and memory deficits [1], and the abnormal deposition of Aβ in the brain causes significant learning and memory impairment in mice [25]. Our study also confirmed that, compared with the control group, Aβ31-35 led to prolonged escape latency and decreased time spent and traveled distance in the target quadrant in the Morris water maze test, suggesting that Aβ31-35 impaired learning and memory capacity in C57BL/6 mice.
Extensive evidence has shown that learning and memory impairment in AD is mainly caused by synaptic dysfunction and abnormal hippocampal synaptic plasticity [26]. SYP, a major calcium-binding protein of the synaptic vesicle membrane, accurately reflects the distribution, number, and density of synapses. Y-maze experiments have shown that increased hippocampal SYP levels contribute to new object recognition and learning and Fig. 6 The change in the expression of Per2 after interference with Per2. (a) A fluorescence microscope was used to determine the optimal multiplicity of infection (MOI). Scale bar = 100 μm. (b) Typical diagram of a fluorescence microscope at an MOI of 60, representative Western blot and quantification analysis of PER2. Scale bar = 50 μm. Data are expressed as means ± SEM (n = 6 per group). *P < 0.05 compared with the control group memory improvement in mice [27]. GAP-43, a neuronspecific protein, is located in the axon and maintains synaptic morphology [28]. GAP-43 plays an important role in synaptic remodeling, which forms the basis of learning and memory [24]. Studies have shown that the level of SYP and GAP-43 protein expression decreases and synaptic dysfunction occurs in the brains of AD patients [29]. The results of our study also confirmed that SYP and GAP-43 proteins were significantly reduced by Aβ31-35 in HT22 cells, indicating that Aβ could induce the learning and memory dysfunction in AD. However, there is no effective treatment to improve learning and memory.
Numerous studies have shown that a normal circadian rhythm is essential for learning and memory maintenance [3]. C57BL/6 mice kept in a normal light-dark cycle can reach the hidden platform more easily in the Morris water maze [3]. Under constant light conditions, the Morris water maze test showed that mice with circadian rhythm disorders exhibit spatial learning impairments [30]. The biological circadian rhythm system is regulated by a transcriptional feedback loop (TTFL) [31]. The rhythmic expression of circadian genes such as Per1, Cry1, and Bmal1 is weakened in Per2 mutant mice [32]. Research has shown that circadian rhythm disorder often occurs very early in AD patients [33]. Furthermore, studies have found that Tg2576 transgenic mouse models of AD exhibit wheel-running rhythm disruption, a prolonged free-running period [34], and abnormal expression of circadian-clock genes under constant darkness conditions [35]. Studies have shown that Aβ could reduce the transcription of Per2 by degradation of BMAL1 and CBP [9], which is consistent with our findings in the present study. In this study, we found that intrahippocampal injections of Aβ31-35 induced unclear movement/rest phases and a longer free running period than that in control group, as shown by a mouse running wheel behavioral experiment. We also detected the expression of Per1 and Per2 in HT22 cells after Aβ31-35 exposure and found that Aβ31-35 could induce abnormal expression of Per1 and Per2 genes, showing that the expression of Per1/Per2 mRNA and protein decreased significantly at CT12(Per1)/CT16(Per2). Indeed, the expression peaks of the protein and the mRNA should have a time lag. We assumed that the reason why the expression of both Per1 mRNA and PER1 protein differed significantly in CT12 was that Per1 mRNA was measured every four hours. In order to further explain the relationship between the Per1 mRNA and PER1 protein, we added the CT10 time point and found that Aβ31-35 caused a significant decrease in Per1 mRNA expression at CT10. Decreased PER1 protein levels induced by Aβ31-35 were observed at CT12. Hence, there is a time lag between the decreased PER1 protein and Per1 mRNA. Similarly, we added the CT14 time point and found that the expression of Per2 mRNA was remarkably decreased by Aβ31-35 (Additional file 2: Figure S2). Hence, the decrease of Per2 mRNA and PER2 protein has a time lag. Further, JTK_CYCLE found that Per1 mRNA expression in HT22 cells did not have a circadian rhythm and Per2 mRNA expression had a circadian rhythm, so we decided to focus our attention on the role of Per2. Per2 mRNA expression in hippocampal tissue exhibited circadian rhythms in the control group In order to confirm the role of circadian rhythm disorder in learning and memory, LV-shPer2 was used to suppress the expression of the Per2 gene. A previous study showed that Per2-mutant mice exhibited abnormal long-term potentiation (LTP) in the hippocampus [36]. In the present study, the results of a wheel-running test in a DD environment showed that downregulation of circadian clock gene Per2 in the hippocampus caused significant circadian rhythm abnormalities. After silencing Per2 with LV-shPer2 in HT22 cells, we found that the expression of Per1 mRNA was reduced remarkably. These results suggested that silencing of Per2 expression in the hippocampus and HT22 cells led to disturbance of the endogenous circadian rhythm and abnormal expression of clock genes. The Morris water maze test and SYP/GAP-43 protein detection showed that the change in the circadian rhythm induced by Per2 deficiency resulted in the decline of learning and memory capacity in mice. A previous study showed that Per1 is essential for the formation of memory [21]. According to the paper, deletion of HDAC3 in the hippocampus, which increases acetylation at the Per1 promoter and expression of Per1 mRNA in response to learning, does not affect the circadian rhythm of young or old mice, indicating that the Per1 gene in the hippocampus could regulate synaptic plasticity and memory formation in a circadian rhythm-independent manner [21]. Whether Per2 in the hippocampus affects learning and memory in a circadian rhythm-independent way will be another interesting topic worth researching further. In addition, it has been reported that hippocampal Per1 plays a critical in memory formation by modulating CREB phosphorylation [37]. The damaged memory capacity in Per2-mutant mice is due to the downregulation of p-CREB [36]. Several studies have shown that Aβ could modulate the p-CREB expression in the hippocampus [38]. Therefore, we speculated that CREB phosphorylation was involved in the regulation of Per1 and Per2 expression on learning and memory in hippocampus.
At present, there is no effective treatment for the circadian rhythm disorder in AD patients. The potential relationship between AD and T2DM has been confirmed in recent years [39], and researchers have tried to apply insulin-based treatment strategies for T2DM, such as GLP-1 and GIP analogs, to AD [11]. GLP-1 and GIP exert their effects by binding to their specific receptors, the GLP-1 receptor (GLP-1R) and GIP receptor (GIPR), which are widely distributed in the brain [40]. Our previous experiments also demonstrated that Exendin-4 could improve the Aβ31-35-induced deterioration of learning and memory function [17]. However, the GIP analogue D-Ala2-GIP could reduce the Aβ plaque burden in the brain [41] and improve the learning and memory dysfunction of APP/PS1 double transgenic mice [42]. DA-JC1 is a novel dual GLP-1R/GIPR receptor agonist that simultaneously activates GLP-1R and GIPR and has equal affinity for both receptors [43]. Compared with the GLP-1R agonist, DA-JC1 has a stronger effect on promoting insulin release and lowering blood glucose [14]. Studies have demonstrated that DA-JC1 exerts a neuroprotection on MPTP-induced Parkinson's disease model mice [16]. However, whether DA-JC1 can alleviate the Aβ-induced decline in learning and memory abilities and circadian rhythm disorder has not been reported. A previous study showed that, as a GLP-1 receptor agonist, liraglutide could attenuate the overexpression of PER1, PER2, and CRY1 protein and partially restore the circadian of T2DM mice [44]. Our previous study showed that Exendin-4 improved Aβ31-35-induced circadian rhythm disorder and learning and memory dysfunction in mice [17]. The present study demonstrated for the first time that DA-JC1 could improve the learning and memory impairment and circadian rhythm disorder in mice induced by Aβ31-35. Specifically, DA-JC1 shortened the escape latency in the Morris water maze and prolonged the percentage of time spent and distance traveled in the target quadrant. Meanwhile, DA-JC1 significantly increased the expression of learning-and memory-related proteins SYP and GAP-43 in HT22 cells. In addition, the results of the running wheel test showed that pretreatment with DA-JC1 improved the circadian rhythm disorder of mice and restored the abnormal expression of Per1 and Per2 clock genes in HT22 cells and Per2 mRNA in mouse hippocampal tissue. Further, we used lentiviral vectors expressing shRNA to downregulate Per2 expression and found that DA-JC1 could no longer improve the learning and memory impairment of mice induced by Aβ31-35 after silencing of Per2 expression, indicating that Per2 in the hippocampus was involved in DA-JC1's improvement of Aβ31-35-induced learning and memory impairment in mice. The underlying mechanisms behind DA-JC1 cannot improve learning and memory defects without Per2 require further study. The outcome of this ongoing research may provide a novel therapeutic intervention for AD in the future.