extfieldsofstudy: Biology Medicine

text:
Connectomics of Morphogenetically Engineered Neurons as a Predictor of Functional Integration in the Ischemic Brain

Recent advances in cell reprogramming technologies enable the in vitro generation of theoretically unlimited numbers of cells, including cells of neural lineage and specific neuronal subtypes from human, including patient-specific, somatic cells. Similarly, as demonstrated in recent animal studies, by applying morphogenetic neuroengineering principles in situ, it is possible to reprogram resident brain cells to the desired phenotype. These developments open new exciting possibilities for cell replacement therapy in stroke, albeit not without caveats. Main challenges include the successful integration of engineered cells in the ischemic brain to promote functional restoration as well as the fact that the underlying mechanisms of action are not fully understood. In this review, we aim to provide new insights to the above in the context of connectomics of morphogenetically engineered neural networks. Specifically, we discuss the relevance of combining advanced interdisciplinary approaches to: validate the functionality of engineered neurons by studying their self-organizing behavior into neural networks as well as responses to stroke-related pathology in vitro; derive structural and functional connectomes from these networks in healthy and perturbed conditions; and identify and extract key elements regulating neural network dynamics, which might predict the behavior of grafted engineered neurons post-transplantation in the stroke-injured brain.

INTRODUCTION
Stem cell therapy for ischemic stroke may extend the therapeutic window from the acute into the sub-acute and chronic stage. As such, it is a particularly interesting approach, considering that more than 80% of stroke patients are de facto not eligible for the standard clinical treatment options, i.e., thrombolysis or thrombectomy (1). Numerous animal studies have demonstrated the potential of stem cell therapy alone, or in combination with in situ tissue engineering strategies and/or pharmacotherapeutics, for promoting functional restoration after stroke.
The rationale behind stem cell therapy is that it can promote functional recovery through a range of possible mechanisms of action, including neuroprotection, modulation of the inflammatory response, cell replacement, remyelination, tissue/vascular remodeling and de novo neurogenesis (2)(3)(4)(5)(6)(7)(8). Although promising and valuable in the quest of elucidating relevant recovery mechanisms at the experimental level, clinical translation of stem cell-based approaches tends to be largely confounded by significant challenges. These include poor graft survival and integration with the host tissue, which indeed is hardly surprising, given the intricacies inherent in aspiring to create safe, functional in situ biointerfaces that could effectively re-establish functional connectivity in multiple foci (9)(10)(11)(12). As a result, numerous past and ongoing clinical trials of various stem cell-based therapies have largely failed to fully confirm preclinical findings by promoting significant and/or longlasting gain of motor, sensory, or cognitive function in stroke patients (10,11,(13)(14)(15).
Apart from the conceivable limitations of extrapolating findings from animal studies to the clinic, a substantial barrier to clinical translation is the lack of a thorough understanding of the underlying mechanisms determining cell graft behavior posttransplantation in the ischemic brain. This is further confounded by the intrinsic complexity of stroke lesions and, with regard to cell replacement and functional integration of the engrafted cells, also the lack of direct empirical evidence supporting neuronal replacement in human patients (1).
It is also worth considering the potential role of endogenous plasticity in response to ischemic injury, not least, the manner in which associated mechanisms may influence transplant behavior (16). Plastic responses after stroke can be demonstrated as neurogenic niche activation and cytogenesis in the ipsilesional brain hemisphere, as well as rewiring of surviving neural networks and recruitment of intact synapses contralateral, but also ipsilateral to the lesion (17)(18)(19)(20)(21)(22). Such plastic responses and, not least, concomitant inflammatory processes triggered by brain ischemia, may conceivably play a significant role in determining functional outcomes after stroke (12,23,24). The underlying mechanisms regulating such responses are however unclear and, consequently difficult to harness in an appropriate or timely manner. Furthermore, the fact that intrinsic neuroplasticity can be adaptive, but also maladaptive, suggests that any attempt to harness it that fails to fully comprehend or suitably engage fundamental underlying mechanisms may inadvertently exacerbate lesion-induced deficits rather than contribute toward functional restoration.
Several questions therefore arise that warrantee rigorous discussion in the scientific community. In this review, we aim to contribute to this discussion by providing a concise overview of novel and emerging theoretical and methodological perspectives which may be significant for improving the robustness of pre-clinical studies with a view to clinical translation. Specifically, we propose the investigation of in vitro engineered neural networks in the context of connectomics and discuss how morphogenetic neuroengineering can be supported by advanced interdisciplinary approaches, including in vitro electrophysiology, microfluidics, and computational modeling, to obtain robust preclinical models that can promote our understanding of cell replacement therapy for stroke beyond the state-of-the-art.

MORPHOGENETIC NEUROENGINEERING
The differentiation and development of projection neurons in the mammalian neocortex is regulated by tight molecular control, which determines and orchestrates sequential cell fate decisions over different temporospatial scales [reviewed in Greig et al. (25)]. An understanding of fundamental mechanisms regulating these processes led to the development of morphogenetic neuroengineering approaches based on controlled expression of transcription factors (26,27). In 2002, a proof-of-principle study by the Göetz lab demonstrated that the Pax6 gene controls the neurogenic potential of radial glia, and also that its forced expression can induce astrocytes to a neuronal fate in vitro (28). A few years later, the same group showed that upregulation of Olig2 expression after brain injury, including focal ischemia, suppresses Pax6 expression, while in vivo transduction with a dominantnegative form of Olig2 in the acute and chronic phase after injury can induce neurogenesis in the neocortex (29).
A major barrier in morphogenetic neuroengineering with a view to clinical translation for cell replacement therapy was broken by Sinya Yamanaka's research. In a seminal paper in 2006, Yamanaka and Takahashi demonstrated conversion of adult somatic cells into induced pluripotent stem cells (iPSCs) after transduction with only four genes (Oct4, Sox2, Klf4 and c-Myc) (30). This method paved the way toward autologous sourcing and generation of theoretically unlimited numbers of stem cells applicable to a range of possible therapeutic approaches in regenerative medicine, including treatment of central nervous system (CNS) lesions, such as ischemic stroke.
Recent advances in cell reprogramming technologies have led to the development of efficient, reproducible, high-yield protocols for the generation of iPSCs and induced neural stem cells (iNSCs), as well as protocols for the generation of induced neurons (iNs) and specific neuronal subtypes, including spinal motoneurons, dopaminergic, cholinergic, and medium spiny neurons, and also cortical neurons, by direct conversion of somatic cells (31)(32)(33)(34)(35)(36)(37); reviewed in Gascon et al. (38). Such direct conversion protocols bypass the pluripotency state through forced expression of lineage-specific transcription factors regulating brain development and may also effectively preserve the age-related and epigenetic imprint of the cell (31,39). Similar principles can be applied for direct reprogramming of glia, including astrocytes, NG2 glia, microglia, and pericytes, into neurons (40)(41)(42)(43)(44). Interestingly, a number of studies have also demonstrated in vivo reprogramming of resident brain and spinal cord astrocytes and endogenous neural progenitors into neurons (44)(45)(46)(47)(48)(49)(50)(51).
Reprogramming through the iPSC/iNSC state or by direct conversion is highly relevant for cell-based therapies for brain ischemia. A number of studies have demonstrated the potential of iPSC and iNSC-derived neurons for cell replacement therapy in stroke (4,52). Furthermore, neurons derived from immature progenitors and pluripotent cells have the potential to establish long-range target-specific functional connections in the adult mammalian CNS (49,(53)(54)(55)(56)(57) reviewed in Wuttke et al. (58).
However, unequivocal evidence of functional integration of iPSC/iNSC derived neurons in the ischemic brain post transplantation is scant, not least regarding the potential of these cells to establish long-term efferent connections in a target-specific manner (1). Tornero and co-authors were the first to show that cortical neuronal progenitors, differentiated from human fibroblast-derived iPSCs, survive after intracortical transplantation in the rat brain after stroke and also receive afferent inputs, as suggested by observed monosynaptic responses from the grafted neurons after stimulation of the intact cortical region adjacent to the graft (59). Furthermore, in a recent study, the same group demonstrated that transplanted iNSC-derived neurons can functionally integrate with the local thalamocortical circuitry and receive direct synaptic inputs from the relevant brain regions (60).
Taken together, such evidence suggests that the state-ofthe-art morhogenetic neuroengineering approaches for the generation of neuronal types relevant for cell replacement therapy in stroke hold promise. Their potential for clinical translation, however, is not without caveats. A fundamental, currently unresolved, question as whether transplanted engineered neurons can promote improved functional outcomes after stroke is the extent to which they can morphologically and functionally integrate with the host tissue.
Several related questions arise: Do engineered neurons have the capacity to establish efferent connections, in addition to afferent ones, post-transplantation? If so, where in the brain are transplanted neurons likely to project and form synapses? How does the transplant respond to evolving stroke related pathology, including the spontaneous reorganization of the relevant neural circuitry after the injury, as well associated dynamic changes at the micro-, meso-, and macroscale? Is it possible to anticipate such responses and, importantly, predict whether functional integration of the transplanted neurons in the host brain will elicit adaptive or maladaptive processes?

Adaptive and Maladaptive Neuroplasticity
To achieve therapeutic interventions for stroke beyond the state-of-the-art we need to consider stem cell therapy in the context of the extremely complex, highly interconnected structural and functional circuitry of the human brain, especially the altered, highly plastic, structure-function relationships triggered by an ischemic lesion. Endogenous neuroplasticity after stroke and its relevance for the functional integration of morphogenetically engineered transplants to elicit recovery of motor, sensory, or cognitive deficits as a result of brain ischemia, can be briefly discussed in the context of Hebbian and homeostatic mechanisms.
During development, the CNS is characterized by a high level of plasticity, where functional brain networks and circuits are shaped by Hebbian mechanisms, such as long-term potentiation (LTP) and long-term depression (LTD) (61,62) constituting the synaptic basis of associative learning (63). These processes are regulated by evolutionarily conserved mechanisms and involve functional and structural changes which occur in a well-orchestrated spatiotemporal manner. However, once development has been completed, Hebbian mechanisms alone cannot explain how the mature brain maintains normal function. In the same manner, Hebbian laws per se cannot sufficiently explain plastic network responses, such as synaptic scaling (64,65), which are observed following externally induced perturbations. This suggested that there may be another form of plasticity underlying such responses. Compelling experimental evidence over the last two decades supports that another form of plasticity, i.e., homeostatic plasticity, does exist (64,(66)(67)(68)(69). Indeed, homeostatic plasticity operates in tandem with Hebbian plasticity along complex temporal and spatial scales and serves to maintain normal neural network function as well as regulate network responses to perturbation (67,70).
It is well-documented that any major disturbance to normal neural network function tends to result in severe, permanent functional deficits, but also trigger adaptive and maladaptive network responses, which are demonstrated as changes in network structure and function (12,18,19,66,(69)(70)(71)(72)(73)(74). Such alterations may represent various underlying forms of neuroplasticity, which involve both homeostatic and Hebbian mechanisms (67,75,76), and which can be described as morphology-activity, (i.e., structure-function) relationships. Such relationships are highly complex and, as a result, poorly understood. However, elucidation of how different forms of plasticity may result in adaptive or maladaptive neural network responses and, thereby, how such processes may promote or hinder functional restoration after a perturbation such as stroke is of fundamental importance for our ability to achieve functional repair.
As mentioned earlier, plastic responses to an ischemic event include spontaneous functional recovery (77), rewiring of surviving neuronal networks and axonal ramification, and the recruitment of intact synapses post-lesioning (78), demonstrated as intra-and interhemispheric neural network remodeling (74). Furthermore, there is increasing consensus as to the likelihood that such responses are also influenced by evolving inflammatory processes (12). The underlying mechanisms regulating such responses largely involve structural as well as functional changes in brain circuits closely associated with the ones directly affected by stroke. These circuits can further be engaged and modified through experience-dependent plasticity (17,79).
It is a reasonable assumption to make that there is a critical period of increased neuroplasticity after stroke, which can be harnessed to promote functional recovery, as exemplified in a number of preclinical as well as clinical studies (12,17,77,(80)(81)(82)(83)(84). Moreover, recent evidence suggests that recovery after stroke can be mediated through the engagement of neural networks in a functional hierarchy both in the contralesional as well as ipsilesional brain hemisphere and also upstream as well as downstream of the lesion (85). Furthermore, it is becoming increasingly evident that any cortical remapping that may occur after stroke is both activity dependent, but also based on competition (86).

Neural Transplants as Part of the Brain Connectome
Where does cell replacement therapy fit in this context? To seek answers to this question, it is important to consider the behavior of engineered neural transplants in the ischemic brain in terms of connectomes (87,88) i.e., the changing structurefunction relationships and complex interplay between affected and intact neural ensembles in the brain in the context of evolving stroke pathology.
Highly relevant insights as to how the brain connectomes underpin the behavior of a neural system and determine functional outcome after a perturbation can be found in an excellent review by Fornito and co-authors (89). In this paper, the authors discuss how the highly interconnected, complex topology of the neural architecture of the brain, which is characterized by a fine, coordinated balance between regional segregation and specialization of function, but also highly precise functional segregation and integration of distal neuronal ensembles across multiple temporal scales, can shape the brain's response to perturbations (89)(90)(91)(92)(93). Specifically, brain network topology can determine not only disease progression, but also adaptive or maladaptive responses to pathological perturbations. By applying fundamental principles from graph theory, it is possible to extract key functional and structural elements of the brain's connectome that may explain or predict such responses (94).
According to graph theory, a neural assembly consists of key elements, namely nodes and edges, and as such, metrics that define properties of the graph can be applied to make inferences about the neural connectome, for example, as it is revealed by electrophysiological activity (92,(94)(95)(96). Nodes incorporate neurons, neuronal populations, and macroscopic brain regions, while edges determine structural, functional, or effective connectivity and, as a result of the latter, the directionality of internodal neural communication. In this manner, structural connectivity can be indicative of morphologyactivity relationships between neurons, whereas functional connectivity, which is independent of the physical proximity of the neurons, provides a temporal correlation of their activity. On the other hand, effective connectivity can determine whether there is a causal relationship between the activity of different neurons (94). Topological properties of particular interest include economical wiring, hierarchical modularity, small-world organization enabling functional segregation, integration and specialization through high network clustering and characteristic short path lengths (93,(95)(96)(97)(98)(99)(100), as well as highly-connected network hubs. Connections between hubs can be describes as rich club, i.e., central core connections, if they extend over large anatomical distances and link distinct functional systems (101). As such, rich club connections mediate high-volume network traffic and integrated brain function.

Connectomics of Adaptive and Maladaptive Responses to Brain Ischemia
As a result of high interconnectivity of neural networks and circuits, the damage induced by lesions such as focal cerebral ischemia dissipates in the brain and progressively spreads to affect distal loci (81). This diaschisis phenomenon constitutes a maladaptive response and may explain the deafferentiation and aberrant synchronization observed in brain regions remote from the one directly affected by the stroke (74,89,92). Excitotoxicity thus plays a central part in the damage sustained to these remote nodes after a stroke. Associated maladaptive responses include anterograde and retrograde neuronal degeneration, for example, as a result of neuronal loss, excitotoxicity and impaired axonal transport, but also dedifferentiation. Apart from loss of tissue at the lesion site, neuronal degeneration involves structural deterioration over time of nodes connected to the primary lesion site, while dedifferentiation refers to the gradual loss of specialized function in the affected brain region, followed by increased, non-specialized activity in associated nodes (89,92) (Figure 1A).
On the other hand, adaptive network responses include lateralization, i.e., compensation for lost function by increased structure-function interactions and the engagement of intact neuronal ensembles within the affected system, or within other systems. Other adaptive responses may include neural reserve, a process by which remaining intact tissue in the immediately affected region can sustain the previous level of behavior, and also degeneracy, where a second system, without demonstrating apparent changes, can adequately support the activity of the affected one (89,102). Thus, the effects of a perturbation critically depend on the topological centrality and degeneracy of the affected region, as pathology of central regions can exacerbate maladaptive responses, whereas degeneracy can facilitate adaptive ones (89,95,96). By the same token, spontaneous or induced gain of function after stroke may imply partial restoration of neural networks previously involved in impaired function or, alternatively, a compensatory or substitution mechanism, which is contingent on the recruitment of other networks (74) (Figure 1B).
However, in any perturbed system, not least, the ischemic brain, which is characterized by highly complex pathophysiological mechanisms and associated cellular and molecular cascades, such responses are neither unequivocal, nor mutually exclusive. Furthermore, as mentioned earlier, the resilience of the perturbed system and the manner in which it may reconfigure its structure-function relationships in response to the lesion largely depends on the topological substrates being affected. It follows that a neural transplant, effectively, a new topological element (likely, a node) within the local circuitry, becomes another integral component in the system's connectome. As such, the input and output functions of the transplant node are shaped by other key elements of the connectome, as for example, its interactions with other nodes, in an interdependent, reciprocal manner.

Assessing the Potential of Morphogenetically Engineered Neurons to Become Integrated Within the Connectome
What are the exact processes that determine whether and/or to what extent neurons engineered in vitro (and by the same token, in vivo), have the capacity to become part of the local connectome in a manner that may promote gain of function after stroke?
Detailed study and elucidation of relevant mechanisms in stroke patients is not feasible and is thus de facto limited to methods and analyses based on indirect and often incomplete observations or measures. Relevant research must therefore rely on robust preclinical models. Notwithstanding various excellent studies employing cell replacement strategies, coupled with cutting-edge methods for monitoring and assessment of functional integration of the engineered neurons in experimental stroke animals (16,60), there is currently no unequivocal evidence supporting that these neurons become fully integrated into the ischemic brain. As a result, pertinent questions remain unanswered, especially with regard to the intrinsic capacity of engineered neurons to engage with local circuitry, whether we can predict their responses to evolving pathology, as well as determine whether their morphological and functional integration into the host brain will elicit adaptive or maladaptive responses and, ultimately, promote repair or inadvertently exacerbate the lesion-induced deficits. We may start addressing such questions by combining in vitro morphogenetic neuroengineering with electrophysiology studies and computational modeling.

Reductionist in vitro Paradigms That Capture Complex Network Dynamics in Healthy and Perturbed Conditions
State-of-the-art platforms for the study of in vitro neural networks include microelectrode arrays (MEAs). MEAs represent a breakthrough in in vitro electrophysiology platforms, as they enable direct observation of evolving network dynamics through extracellular recordings, as well as disease modeling and modulation of network activity by electrical, chemical, opto-or chemogenetic manipulation to selectively perturb network function or engage its plasticity (94,(103)(104)(105)(106)(107)(108)(109)(110)(111).
This approach largely exploits intrinsic attributes of in vitro neural networks, including emergence/morphogenesis, as a result of cell behaviors driven by local cell-cell interactions, and selforganized criticality (SoC) (112). A universal characteristic of in vitro cultured neurons, irrespective of source (i.e., rodent or human) or specific subtype, is that they self-organize into functional complex networks. This spontaneous process, which occurs in the absence of any external instructive influence (113), involves the network's gradual transition through distinct morphology-activity states underscored by increasing structural and functional complexity as a result of emerging neuronal activity, axonal elongation and pathfinding, synapse formation and pruning (113,114). Over time, the network gains morphological and functional maturity, ultimately reaching SoC, a critical state characterized by a fine balance between excitation and inhibition (113,(115)(116)(117)(118). Once at the SoC state, the neural network exhibits neuronal avalanches, i.e., characteristic cascades of activity defined by rich, stable spatiotemporal patterns and power-law distributions of variables (114,119). Criticality has been closely, yet not exclusively, associated with self-organization (112,(120)(121)(122)(123)(124).
How does SoC displayed by in vitro neural networks relate to normal or impaired brain function? The idea that the brain operates in a near-critical state is not new (119, 125, 126), yet the presence of SoC states in the brain has, to a certain extent, been the subject of debate until relatively recently (119,(127)(128)(129). However, emerging evidence, including findings from magnetoencephalography (MEG) studies in human subjects, strongly supports the presence of SoC in the brain, not only as a mechanism underlying spatially local or internodal measures of brain activity, for example, as relevant for cortical function, but also as a global phenomenon (123,130). This suggests that within the brain connectome, SoC states play a putative role in information transmission and processing, including segregation and integration of function along different spatiotemporal scales (114,123,124,131). As such, critical states in the brain emerge from the complex underlying morphologyactivity relationships shaping the system's behavior and are stipulated to underscore adaptation processes in the context of neuroplasticity. It is currently unknown how changes in network organization over different spatiotemporal scales, for example, as a result of ischemic insult, may affect such states (114).
In vitro biological substrates that combine morphogenetically engineered neurons with MEAs can be used to obtain insights into such mechanisms. For example, neural avalanches can be observed and recorded as synchronous local field potential (LFP) spikes across multiple electrode locations. Dependent on the number of embedded recording electrodes available on the MEA, which may range from a few dozen (typically 60-120 electrodes) to several thousand, the observed LFPs may arise from neuronal clusters, effectively individual nodes within the network, but also represent single-cell activity, as in the case of very high-density (>11,000 electrodes) complementary metaloxide semiconductor (CMOS) integrated circuit MEAs (118). This effectively means that the derived neural substrates can faithfully recapitulate fundamental aspects of neural network behavior, thus enabling the study of complex network dynamics in reductionist in vitro paradigms. Maintenance of the relevant MEA-based neural networks in optimal culture conditions enables long-term monitoring of network behavior up to several weeks or months (132) (Figure 2).

Verification of Functionality
In light of the above, an immediate application of in vitro morphogenetically engineered neurons on MEAs can be the validation of the neurons' functionality prior to transplantation in the ischemic brain. This is a crucial but often overlooked parameter, given that fundamental intrinsic properties of engineered neurons, such as self-organization, spontaneous firing activity, or capacity to reach SoC states, can be expected to provide a gauge as to their potential to survive and integrate with the host tissue post-transplantation. As such, electrophysiological recordings from engineered neurons on MEAs is a highly complementary method to transcriptional analyses of such neurons after reprogramming and should constitute an integral part of their characterization before proceeding to in vivo studies.
Importantly, apart from verification of the inherent capacity of in vitro engineered neurons to self-organize into functional networks, reductionist in vitro paradigms such as MEA-based biological substrates also constitute a powerful tool for assessing the behavior of these networks in healthy and perturbed conditions by enabling the study of their connectomes.
Several recent studies have demonstrated that in vitro neural networks, including human engineered neuronal cultures, demonstrate physiological maturation over time suggestive of complex underlying structure-function relationships (133)(134)(135)(136)(137)(138). Functional maturation can be further enhanced typically by culturing neurons on a feeder layer of astrocytes (139,140), or by adapting the differentiation protocol to generate both neurons and astrocytes (141), thus optimizing neuronal polarization, axonal and dendritic arborization, and synapse formation in the derived networks (142)(143)(144). In this manner, in vitro neural networks recapitulate fundamental topological properties of the brain, including key features mentioned earlier, such as hierarchical modularity and small-world organization (98,100).
Various methods for MEA data analysis can be applied to make inferences about the functional, structural or effective connectivity of the network, as well as its dynamical or critical states (94,145). Such inferences are particularly relevant for obtaining insights as to the state of a neural network (including sub-critical and super-critical states) (113,115,(146)(147)(148) but also for identifying evolving pathology, and predicting the manner in which the network will respond, i.e., adaptive or maladaptive.

Mimicking Stroke-Related Pathology
As mentioned earlier, one of the fundamental yet unanswered questions pertaining to the functional integration of in vitro engineered neurons in the ischemic brain post-transplantation is lack of unequivocal evidence from in vivo stroke models as to the ability of these grafts to extend axons and form efferent connections with appropriate targets. A corollary to the above is the capacity of such grafts to become incorporated in the local circuitry while pathophysiological processes of the injury and/or spontaneous plasticity of the host brain are in progress. MEA-based neural substrates provide an excellent platform for mimicking key aspects of such processes in a controlled manner.
There are currently no reported studies in the literature investigating stroke-related pathology in human engineered neural networks using MEA-based platforms. However, a number of reports have demonstrated the utility of these platforms for CNS disease modeling, often in the context of neurodegenerative disorders, epilepsy, toxicology, and drug screening, as well studies of neural network plasticity and response to selective modulation (108,(149)(150)(151).
Beyond the state-of-the-art modeling of engineered neural network responses to stroke may be achieved by the incorporation of defined topography and/or dimensionality in the MEA-based substrate. For example, a host of different biological and synthetic scaffolds can be applied for bioengineering of in vitro neural networks in threedimensional (3D) cultures as opposed to the conventional two-dimensional (2D) ones (152)(153)(154)(155). Such systems, which may also combine the use of a scaffolding substrates with 3D-rather than planar 2D-MEAs, can help recapitulate structure-function relationships shaped by cell morphology, cell-to-cell interactions, and axonal outgrowth in all directions within the extracellular microenvironment. In this manner, the derived in vitro connectomes can better approximate the micro-, meso-, and macroscale dynamics of the brain, thus enabling self-organized neural network behavior of increased complexity, compared to 2D systems (150,156,157). Importantly, 3D substrates are compatible with co-culture of neurons with other relevant cell types, including astrocytes and microglia, thus adding to the physiological relevance of the assay (142,144,(158)(159)(160)(161)(162).
Hence, the 3D configuration can be used to assess emerging morphology-activity relationships in unperturbed engineered neural networks in vitro, but also to study their responses to stroke related pathology, as for example, after oxygenglucose deprivation or induced excitotoxicity. The versatility and relevance of these platforms for in vitro connectomics of engineered neurons, can further be enhanced with the incorporation of microfluidics devices, which enable in vitro culture of modular neuronal ensembles with definable connectivity at the micro-and nanoscale level.
Custom-designed microfluid devices can be fabricated using a variety of methods including etching techniques, photoand e-beam lithography, embossing, replica molding, and laser photoablation (163). Such systems enable the culture of in vitro neural networks by confining neuronal somata within designated compartments, i.e., nodes, and controlling afferent and efferent inter-nodal connectivity by predefined, directional axonal outgrowth through micropatterned channels only permissible to neuronal axons and neurites (164). As such, microfluidic devices can be superior to conventional culture systems as they enable spatial and temporal control of the neuronal microenvironment (163). Importantly, such microfluidic devices can be interfaced with MEAs, thus enabling longitudinal monitoring of intra-and internodal network dynamics in normal and perturbed conditions. These integrated in vitro platforms may thus constitute a powerful tool for the investigation of the connectomics of morphogenetically engineered neural networks alone, or in co-culture with other relevant cells, including different relevant neuronal subtypes, glia, and microglia (142,158,165,166). A potential application of multi-nodal microfluidic devices integrated with MEAs is to test whether compartmentalized engineered neurons can form integrated multi-nodal functional networks which demonstrate efferent, as well as afferent connectivity. Such studies can thus help address a pertinent, yet unelucidated question regarding engineered neural networks, namely, whether they can form efferent synapses. Furthermore, the topology and molecular/flow gradients of the microfluidic platform can be exploited to induce disease-related pathologies in a selective or controlled manner and monitor dynamic intra-and inter-nodal responses over time (167,168). Added microtopography features, such as the incorporation of synaptic chambers (169), enable monitoring of axons and synapses at cross-sections between nodes, and also facilitate added manipulations, as for example axotomy (170,171). Depending on electrode alignment in the MEA interface, such microfluidic designs can also enable monitoring of spike propagation along axons between nodes (172), as well as selective electrical stimulation.

Distinctive Advantages of in vitro Models
Clearly, advanced in vitro modeling platforms are highly versatile and can recapitulate complex morphology-activity relationships underpinning brain function (173)(174)(175). Such in vitro systems afford unique scope for mimicking stroke-related pathology and determining dynamic behavior of engineered neurons in the context of functional integration. Thus, although in vitro models are reductionist in nature, they are by no means simplistic and, compared to in vivo models, they enable specific manipulations and observations in a highly controlled manner. Especially with regard to connectomics studies, in vitro models have the distinctive advantage of allowing the study of emerging, dynamic network behavior at the micro-and mesoscale across large populations of neurons in different assemblies, including their internodal interactions (166,176). Advanced in vitro models are thus highly complementary to in vivo ones, constituting valid alternatives and providing valuable insights that can instruct the design of in vivo stroke transplantation studies with improved predictive validity for clinical translation. As such in vitro modeling platforms are also aligned with the 3R principles (i.e., Replace, Reduce, Refine) pertaining to the use of experimental animals.

Deep Learning; Making Inferences and Predictions About Behavior
Notwithstanding the tremendous potential afforded by these advanced in vitro platforms for studying engineered neural networks in the context of stroke modeling, it must be emphasized that MEA-based electrophysiology tends to generate very high volumes of data (typically, a standard 10 min recording from a 60-electrode MEA can generate 0.5 GB of data; indicatively, the corresponding data volume increases to 1,5 GB when using a 4,096-electrode MEA). As a result, the study of connectomes, which requires extraction of functional, structural and effective connectivity and, by the same token, inference about the underlying neural network state, or prediction about its dynamic responses to stroke-related pathology, including anticipated behavior post-transplantation in vivo, cannot be achieved with standard software analysis methods. Advanced computational modeling applying deep learning principles is thus necessary.
As mentioned earlier, connectomics analyses may apply graph theory and relevant theoretical models to determine underlying structure-function relationships within a neural network and infer its critical states (94,109,116,117,172). For example, advanced computational modeling may apply principles from cellular automata (CAs) or random Boolean networks (RBNs), which examine the relationships between constituent key elements of a system based, respectively, on proximal or random connections (177). Furthermore, machine learning or deep learning approaches, such as artificial neural networks (ANNs) and artificial recurrent neural networks (RNNs), are highly relevant computational models for MEA data analysis. Such models take inspiration from biological neural networks (BNNs). Briefly, in these models the neurons, i.e., the computing elements of the system, are arranged in layers through which information flows in a feed-forward manner. Interestingly, temporal dynamics of the systems can be captured by RNNs by assigning recurrencies (cycles) within the connection topology of the neurons in the system. As a result, the system possesses a memory of previous inputs; in other words, the activation state of the network at a given time represents a function of its previous activation states. As such, an RNN can be seen as an untrained reservoir of dynamics that operates in a near-chaotic state. This enables control of the system by selecting only a single linear redout layer for training (178).
RNNs are thus well-suited to capturing dynamic network behavior of in vitro neural networks, including their critical states. These attributes of RNNs make them an excellent computational paradigm for the investigation of mechanisms by which neuronal populations, including engineered neural networks, solve various computational problems in healthy and perturbed conditions (178)(179)(180)(181)(182). In this way, we can start addressing fundamental questions that can help determine the functional capacity of engineered neurons. Moreover, such models can be applied to decipher as well as predict the behavior of engineered neurons in response to stroke-related pathology in vitro and also post-transplantation in vivo. Importantly, the relevant computational models can be applied to make inferences about underlying critical states, including spontaneous and induced plasticity of these networks.
Finally, closed-loop hybrid systems are highly relevant in this context as they can be used for advanced simulations of spontaneous and induced plasticity, including bi-directional learning. For example, by interfacing an engineered neural network on an MEA with a simulated agent (i.e., computer hardware) we could elicit real-time agent behavior powered by the neural network using reservoir computing (183). Furthermore, by selecting a pacemaker node within the engineered neural network as the target for electrical stimulation, we were able to alter the pacemaker activity in a manner suggestive of LTP, and at the same time demonstrate learning behavior in the simulated agent (183). Other reported studies have also demonstrated the capacity of embodied neural network cultures for goal-directed behavior and learning (184)(185)(186). Such approaches are highly promising for the future development and application of relevant experimental paradigms for in vitro and in silico assessment of the endogenous as well as induced plasticity of engineered neural network, as for example, in terms of guided closed-loop neuromodulation approaches post-transplantation.

CONCLUSIONS
In this review, we have discussed how the combination of interdisciplinary methods and theoretical principles can help develop robust pre-clinical experimental paradigms that can help validate the functional capacity of morphogenetically engineered neurons as well as provide significant insights as to their potential for promoting functional outcomes after transplantation in the stroke lesioned brain. This integration of approaches is both timely and necessary and can be expected to make significant contributions toward the safe translation of stem cell therapy in the clinic.

AUTHOR CONTRIBUTIONS
AS and IS contributed equally to all aspects pertaining to the design and preparation of this manuscript, including idea for the review, literature search and selection, writing, editing, and finalizing the manuscript.


extfieldsofstudy: Medicine Biology

text:
Two new Erythrophylloporus species (Boletaceae) from Thailand, with two new combinations of American species

Abstract Erythrophylloporus is a lamellate genus in the family Boletaceae that has been recently described from China based on E.cinnabarinus, the only known species. Typical characters of Erythrophylloporus are reddish-orange to yellowish-red basidiomata, including lamellae, bright yellow basal mycelium and smooth, broadly ellipsoid, ellipsoid to nearly ovoid basidiospores. During our survey on diversity of Boletaceae in Thailand, several yellowish-orange to reddish- or brownish-orange lamellate boletes were collected. Based on both morphological evidence and molecular analyses of a four-gene dataset (atp6, tef1, rpb2 and cox3), they were recognised as belonging in Erythrophylloporus and different from the already known species. Two new species, E.paucicarpus and E.suthepensis are therefore introduced from Thailand with detailed descriptions and illustrations. Moreover, two previously described Phylloporus species, P.aurantiacus and P.fagicola, were also revised and recombined in Erythrophylloporus. A key to all known Erythrophylloporus species is provided.

Introduction
Most fungi in the family Boletaceae are pileate-stipitate with poroid hymenophore, but some have a lamellate hymenophore. Lamellate Boletaceae are currently classified in four genera, Phylloporus Quél, which contains about 84 species worldwide, Phylloboletellus Singer from South America and Mexico, the two recently described genera Phylloporopsis Angelini et al., from the New World and Erythrophylloporus Ming Zhang & T.H. Li from Asia, each of which circumscribes only one species (http:// www.indexfungorum.org, Farid et al. 2018;Zhang and Li 2018).
The genus Erythrophylloporus was recently described from China, with E. cinnabarinus Ming Zhang & T.H. Li as the type species. According to Zhang & Li (2018), the typical characters of the genus are orange to reddish-orange basidiomes, reddish-orange to yellowishred lamellae turning greyish-green when bruised, bright yellow to orange yellow context staining blackish-blue to dark blue when exposed, bright yellow basal mycelium, smooth and broadly ellipsoid to nearly ovoid basidiospores and yellowish-brown pigmented cystidia. During our survey on the diversity of Boletaceae in Thailand, several collections of lamellate boletes were discovered. Some collections were recognised to belong to Erythrophylloporus by possessing yellowish-orange to deep orange to reddish-orange basidiomata with bright yellow basal mycelium and smooth basidiospores. We also found that two described Phylloporus species, P. aurantiacus Halling & G.M. Mueller from Costa Rica and P. fagicola Bandala from Mexico (Halling et al. 1999, Montoya andBandala 2011), share similar morphological characters with the genus Erythrophylloporus, but until now, have not been included in a molecular phylogeny. In this study, a combination of phylogenetic and morphological evidence indicated that our Thai collections were new species, that, together with the two aforementioned American Phylloporus species, belong in Erythrophylloporus. Therefore, we introduce two new species with detailed descriptions and illustrations and propose two new combinations. As some of the species we studied have some characters that do not fit with the protologue of the genus, we emend its description.

Specimen collecting
Specimens were obtained and photographed from community forests and Doi Suthep-Pui National Park, Chiang Mai Province, northern Thailand during the rainy season in 2015 to 2016. The specimens were wrapped in aluminium foil and taken to the laboratory. After description of macroscopic characters, all specimens were dried in an electric drier at 45-50 °C. Examined specimens were deposited in the herbaria CMUB, MFLU, BKF or BR (Index Herbariorum; Thiers, continuously updated).

Morphological studies
Macroscopic descriptions were made based on detailed field notes and photos of fresh basidiomata. Colour codes follow Kornerup and Wanscher (1978). Macrochemical reactions (colour reactions) of fresh basidiomata were determined using 10% potassium hydroxide (KOH) and 28-30% ammonium hydroxide (NH 4 OH) in water. Microscopic structures were observed from dried specimens mounted in 5% KOH, NH 4 OH, Melzer's reagent or 1% ammoniacal Congo red. A minimum of 50 basidiospores, 20 basidia and 20 cystidia were randomly measured at 1000× with a calibrated ocular micrometer using an Olympus CX51 microscope. The notation '[m/n/p]' represents the number of basidiospores m measured from n basidiomata of p collections. Dimensions of microscopic structures are presented in the following format: (a-)bc-d (-e), in which c represents the average, b the 5 th percentile, d the 95 th percentile and a and e the minimum and maximum values, respectively. Q, the length/width ratio, is presented in the same format. A section of the pileus surface was radially and perpendicularly cut at a point halfway between the centre and margin of the pileus. Sections of stipitipellis were taken from halfway up the stipe and longitudinally cut, perpendicularly to the surface. All microscopic features were drawn by free hand using an Olympus Camera Lucida model U−DA, fitted to the microscope cited above. For scanning electron microscopy (SEM), a spore print was mounted on to a SEM stub with double-sided tape. The sample was coated with gold, examined and photographed with a JEOL JSM-5910 LV SEM (JEOL, Japan).

DNA isolation, PCR amplification and DNA sequencing
Genomic DNA was extracted from fresh tissue preserved in CTAB or about 10-15 mg of dried specimens using a CTAB isolation procedure adapted from Doyle and Doyle (1990). Portions of the genes atp6, tef1, rpb2 and cox3 were amplified by the polymerase chain reaction (PCR) technique. The tailed primers ATP6-1M40F and ATP6-2M (Raspé et al. 2016) and the primer pairs EF1-983F/EF1-2218R (Rehner and Buckley 2005) and bRPB2-6F/bRPB2-7.1R (Matheny 2005) were used to amplify atp6, tef1 and rpb2, respectively. PCR conditions were the same as in Raspé et al. (2016). Part of the mitochondrial gene cox3 was amplified with the primers COX3M1-F and COX3M1-R , using KAPA2G™ Robust HotStart polymerase (Kapa Biosystems, Wilmington, MA, USA) and the following PCR programme: 2 min 30 s at 95 °C; 35 cycles of 25 s at 95 °C, 30 s at 48 °C, 30 s at 72 °C; 3 min at 72 °C. PCR products were purified by adding 1 U of Exonuclease I and 0.5 U FastAP Alkaline Phosphatase (Thermo Scientific, St. Leon-Rot, Germany) and incubated at 37 °C for 1 h, followed by inactivation at 80 °C for 15 min. Sequencing was performed by Macrogen Inc. (Korea and The Netherlands) with PCR primers, except for atp6, for which universal primers M13F-pUC(-40) and M13F(-20) were used; for tef1, additional sequencing was performed with two internal primers, EF1-1577F and EF1-1567R (Rehner and Buckley 2005).

Alignment and phylogeny inference
The sequences were assembled in GENEIOUS Pro v. 6.0.6 (Biomatters) and introns were removed prior to alignment, based on the amino acid sequence of previously published sequences. All sequences, including sequences from GenBank, were aligned using MAFFT version 7 (Katoh and Standley 2013) on the server accessed at http:// mafft.cbrE.jp/alignment/server/.
Maximum Likelihood (ML) phylogenetic tree inference was performed using RAxML-HPC2 version 8.2.10 (Stamatakis 2006) on the CIPRES web portal (Miller et al. 2009). The phylogenetic tree was inferred from a four-partitions combined dataset, using the GTRCAT model with 25 categories. Two Buchwaldoboletus and nine Chalciporus species from subfamily Chalciporoideae were used as the outgroup. Statistical support of clades was obtained with 1,000 rapid bootstrap replicates.
For Bayesian Inference (BI), the best-fit model of substitution amongst those implementable in MrBayes was estimated separately for each gene using jModeltest (Darriba et al. 2012) on the CIPRES portal, based on the Bayesian Information Criterion (BIC). The selected models were GTR+I+G for atp6 and cox3, SYM+I+G for tef1 and K80+I+G for rpb2. Partitioned Bayesian analysis was performed with MrBayes 3.2 (Ronquist et al. 2012) on the CIPRES portal. Two runs of five chains were run for 15,000,000 generations and sampled every 1,000 generations. The chain temperature was decreased to 0.02 to improve convergence. At the end of the run, the average deviation of split frequencies was 0.007058 and the Potential Scale Reduction Factor (PSRF) values of all parameters were close to 1. The burn-in phase (25%) was estimated by checking the stationarity in the plot generated by the sump command.

Phylogenetic analysis
Twenty-five sequences were newly generated and deposited in GenBank (Table 1). The sequences from three specimens, OR0689, OR1135 (E. paucicarpus) and OR0615B (E. suthepensis), were not included in our phylogenic analyses because they were identical to the sequences of the type specimens of E. paucicarpus and E. suthepensis. The alignment contained 906 sequences (179 for atp6, 313 for tef1, 279 for rpb2, 135 for cox3) from 315 voucher specimens and was 2946 characters long (TreeBase number 24078). ML and BI trees showed similar topologies without any supported conflict (Bootstrap Support values, BS ≥ 70% and posterior probabilities, PP ≥ 0.90; Fig. 1). The four-gene phylogram indicated that the included taxa formed seven major clades, representing the Austroboletoideae, Boletoideae, Chalciporoideae, Leccinoideae, Xerocomoideae, Zangioideae and the Pulveroboletus group. Erythrophylloporus cinnabarinus (typus generis) grouped with the two new Erythrophylloporus species, E. paucicarpus and E. suthepensis, in a highly supported clade (BS = 100% and PP = 1). The two New World Phylloporus species (P. aurantiacus voucher REH7271 and P. fagicola voucher Garay215) Description. Basidiomata stipitate-pileate with lamellate hymenophore, small to medium-sized; Pileus subhemispheric to convex when young becoming convex to planoconvex to plano-subdepressed when old, dry, pruinose or velutinous, subtomentose to tomentose, yellowish-orange to red; pileus context vivid yellow to yellowish-orange. Hymenophore lamellae, slightly thick, decurrent, deeply yellowish-orange to deep orange or reddish-orange to orange red or brownish-orange to red. Stipe central to slightly excentric, cylindrical or clavate, yellowish-to reddish-orange to yellowish red, with scattered yellowish-to reddish-orange to red scales on surface, with bright yellow basal mycelium; stipe context solid, yellow to reddish-yellow or yellow with olivaceous Figure 1. Phylogenetic tree inferred from the four-gene dataset (atp6, rpb2, tef1 and cox3), including Erythrophylloporus species and selected Boletaceae using Maximum Likelihood and Bayesian Inference methods (ML tree is presented). The two Buchwaldoboletus and nine Chalciporus species in subfamily Chalciporoideae were used as outgroup. Most of the taxa not belonging to the Pulveroboletus group were collapsed into subfamilies. All generic clades, including one undescribed generic clade in Pulveroboletus group that were highly supported, were also collapsed. Bootstrap support values (BS ≥ 70%) and posterior probabilities (PP ≥ 0.90) are shown above the supported branches.
brown. Staining none or slightly reddening or greening or gradually bluing or dark violet, greyish to blackish-blue when bruised on the basidiomata or context or lamellae. Spore print olivaceous brown. Basidiospores ovoid or ellipsoid to broadly ellipsoid to subovoid, thin-walled, with non-bacillate surface. Basidia clavate to narrowly clavate. Cheilocystidia and pleurocystidia present, subcylindrical or narrowly conical to narrowly fusiform to ventricose with slightly or obtuse apex, thin-walled, sometimes thickwalled, originating more or less deeply in the sub hymenium or from hymenophoral trama, hyaline or sometimes containing yellowish-brown pigments. Pileipellis a subcutis to cutis to trichoderm to palisadoderm, composed of thin to slightly thick-walled hyphae. Remarks. Erythrophylloporus is easily distinguished from other lamellate Boletaceae genera by a combination of the following characters: the intense orange to red colour of the pileus and lamellae; bright yellow basal mycelium; ovoid or ellipsoid to broadly ellipsoid to subovoid basidiospores with non-bacillate surface; pleurocystidia originating more or less deeply in the subhymenium or from hymenophoral trama. Etymology. from Latin "pauci-" meaning few and "carpus" meaning fruits or what is harvested, refers to the low number of basidiomata produced.
Macrochemical reactions. KOH on pileus and stipe surface deep red at first, then red-brown to brown, with pale orange aura on the pileus; brown on pileus context, dark red-brown on stipe context; brownish-orange on hymenophore. NH 4 OH on pileus first red, then orange; on pileus context bluing at first then with a greenish tinge; on stipe surface and context briefly bluing; no reaction on hymenophore.
Habit and habitat. On soil, mostly solitary in dipterocarp forest dominated by Dipterocarpus tuberculatus, D. obtusifolius, Shorea obtusa, S. siamensis, Quercus spp. and Lithocarpus spp. Remarks. E. paucicarpus is characterised by the following combination of features: orange to brownish-to orange-red basidiomata, yellowish-orange lamellae that turn slightly red when bruised; pileus context yellow to yellowish-orange that slowly reddens when exposed and mostly occurring as solitary basidiomata.
In the inferred molecular phylogeny, E. paucicarpus clustered close to E. suthepensis and E. cinnabarinus (65% BS and 1 PP), but the two species are different from   E. paucicarpus in that they have darker lamellae which are orange to orange red or brownish-orange. Moreover, spores of E. paucicarpus are wider and longer (5.9-8 × 4.1-6 µm) than those of E. suthepensis (4.6-5.9 × 3.5-4.5 µm) and, on average, longer than those of E. cinnabarinus (5.5-7 × 4.5-5.5 µm) (Zhang and Li 2018). Erythrophylloporus paucicarpus also differs from both species by the slight reddening of the context and lamellae when exposed or bruised, whereas E. suthepensis context seems unchanging when exposed and lamellae turn blue when bruised. In E. cinnabarinus, the context slowly turns dark violet, blackish-blue to dark blue when exposed and lamellae turn greyish-blue, or greyish-green when bruised (Zhang and Li 2018).
Erythrophylloporus paucicarpus is different from the two New World species by the reddening of the context, whereas in E. fagicola, it turns blue and, in E. aurantiacus, the colour remains unchanged when exposed. Moreover, E. fagicola has somewhat thickwalled (0.8-3.5 µm) pleurocystidia (Montoya and Bandala 2011), which are not found in E. paucicarpus. Although the basidiospores of E. paucicarpus and E. aurantiacus are similar in size (E. aurantiacus = 6.0-7.5 × 4-5.5 µm), they differ in shape, being more ovoid in E. aurantiacus than in E. paucicarpus. Erythrophylloporus paucicarpus also differs from E. aurantiacus by macro-chemical reactions. In the latter, the pileus surface and pileus context are unchanging with NH 4 OH , while in E. paucicarpus, the pileus becomes orange to red and the pileus context initially turns blue then with a greenish tinge. Holotype. THAILAND, Chiang Mai Province, Muang District, Doi Suthep-Pui National Park, 18°48'47"N, 98°55'56"E, elev. 645 m, 25 August 2015, S. Vadthanarat, SV0236, (holotype CMUB, isotype BKF, BR).
Macrochemical reactions. KOH orange-brown on pileus and stipe surface; yellowish-brown on pileus and stipe context and hymenophore. NH 4 OH yellowish-brown on pileus and stipe surface and hymenophore; yellowish on pileus and stipe context.
Morphologically, E. suthepensis is quite similar to E. cinnabarinus in that they have similar colours in pileus and lamellae; the lamellae in both species also turn more or less blue to dark blue when bruised. Erythrophylloporus suthepensis and E. cinnabarinus are also similar, based on some pleurocystidia containing yellowish-brown to dark brown pigments, but those features are not found in E. paucicarpus and in the two New World Erythrophylloporus species (Halling et al. 1999, Montoya andBandala 2011). However, the pleurocystidia containing brown pigments seem to be more frequent in E. cinnabarinus, which also has, on average, larger basidiospores than E. suthepensis (Zhang and Li 2018).
The pinkish-red hymenophoral trama of E. suthepensis was not found in either E. paucicarpus or in the two American Erythrophylloporus species. In our observation of the two American specimens (E. aurantiacus voucher REH7271 and E. fagicola voucher Garay215), we found that the hymenophoral trama was yellowish hyaline when observed in water. The original description of E. cinnabarinus does not mention the colour of the hymenophoral trama and we could not obtain a specimen to observe this character. However, other morphological characters and phylogenetic evidence are enough to differentiate E. suthepensis from E. cinnabarinus.
Our phylogenetic analyses of a four-gene dataset revealed that Phylloporus aurantiacus from Costa Rica and P. fagicola from Mexico clustered in the Erythrophylloporus clade with high support (BS = 100% and PP = 1). Both species possess the distinctive morphological characters of Erythrophylloporus, which include yellowish-orange to reddish-orange basidiomata, orange to orange brown lamellae, bright yellow basal mycelium, ovoid or ellipsoid to broadly ellipsoid basidiospores with smooth surface and subcylindrical to subfusoid to ventricose cheilocystidia and pleurocystidia (Halling et al. 1999, Montoya andBandala 2011). Therefore, the following two new combinations are proposed: close to E. cinnabarinus (typus generis). Morphologically, they are characterised by having yellowish-orange to reddish-to brownish-orange basidiomata with bright yellow basal mycelium and smooth, ellipsoid, broadly ellipsoid to subglobose basidiospores. The other lamellate Boletaceae in Phylloporus, Phylloboletellus and Phylloporopsis are solely similar to the new species by having a lamellate hymenophore instead of a poroid hymenophore. However, Phylloporus differs from Erythrophylloporus species by having whitish-to yellowish-pale brown basidiomata with yellow to golden-yellow lamellae, with off-white to whitish to yellow basal mycelium and most species in the genus have basidiospores with more or less bacillate ornamentation under SEM (Neves & Halling 2010, Neves et al. 2012, Zeng et al. 2013). The single Phylloboletellus species, Ph. chloephorus Singer differs from Erythrophylloporus by having longitudinally ridged basidiospores (Bandala et al. 2004). The sole species of Phylloporopsis, Phy. boletinoides, differs by having beige to olive-cream or olive buff lamellate to subporoid hymenophore, with anastomosing and interveined gills and basal mycelium whitish to yellowish (Farid et al. 2018). Moreover, those genera are phylogenetically distant from Erythrophylloporus. (Bandala et al. 2004, Neves & Halling 2010, Neves et al. 2012, Zeng et al. 2013, Farid et al. 2018. Interestingly, Phylloporus coccineus Corner, described from Singapore (Corner 1970), is similar to Erythrophylloporus species, in that it produces crimson to scarlet, lamellate basidiomata with orange to orange-red lamellae and yellow basal mycelium, broadly ellipsoid to subglobose and smooth basidiospores. It probably should also be transferred to Erythrophylloporus, but we refrain from doing so until specimens become available for molecular study. According to the protologue of P. coccineus, it differs from the newly described Asian species of Erythrophylloporus by having larger basidiospores (7.5-10 × 6.5-8 µm), larger cheilocystidia (70-120 × 10-18 µm) and larger caulocystidia (up to 200 × 10-16 µm) (Corner 1970).
Erythrophylloporus species formed two clades, an Asian species clade (BS = 65% and PP = 1) and a New World species clade (BS = 100% and PP = 1) (Fig. 1). The Asian one contains three species, E. cinnabarinus, E. paucicarpus and E. suthepensis, while the American clade contains the remaining two species E. aurantiacus and E. fagicola. Erythrophylloporus aurantiacus and E. fagicola seem to be genetically very close to each other, much closer than the species in the Asian clade. Only morphological differences between the two species were used to separate them from each other. Erythrophylloporus fagicola produces larger basidiospores than E. aurantiacus and pleurocystidia are somewhat thick-walled (0.8-3.5 µm thick) in E. fagicola, whereas they are thin-walled in E. aurantiacus and the latter has non-staining context, whereas the former has a cyanescent context. However, the descriptions were based on a limited number of collections and more samples are desirable to verify whether the morphological traits observed are good characters differentiating the two species or merely extremes of a continuum in morphological variation within a single species.
Regarding the phylogenetic affinities of Erythrophylloporus, Zhang and Li (2018) reported that it was likely close to the genus Rugiboletus G. Wu & Zhu L. Yang and Lanmaoa G. Wu & Zhu L. Yang, based on a multilocus dataset of nrLSU, tef1, rpb1 and rpb2, although this relationship was not supported in their phylogram. In our phylogeny, based on a multilocus dataset of atp6, tef1, rpb2 and cox3, with wider taxon sampling, Erythrophylloporus also clustered within the Pulveroboletus group, but was sister to Singerocomus with high bootstrap support (96%) but relatively weak posterior probability support (0.86). Singerocomus contains three species, S. atlanticus A.C. Magnago, S. inundabilis (Singer) T.W. Henkel and S. rubriflavus T.W. Henkel & Husbands that have some similar morphological characters to Erythrophylloporus, including red-orange to red pileus and light yellow basal mycelium. The three existing Singerocomus species are clearly different from all known Erythrophylloporus species by having a poroid, non-cyanescent hymenophore (Henkel et. al. 2016, Magnago et al. 2018). However, the hymenophore structure (lamellate vs. poroid) is not sufficient to separate genera in Boletaceae. Phylloporus currently contains both lamellate and poroid species, although some poroid species have already been transferred to another genus, Hourangia (Zhu et al. 2015). Phylogenetic analyses, including the remaining poroid Phylloporus species, are needed to verify their taxonomic position.
Erythrophylloporus putatively forms ectomycorrhizal associations with trees in family Fagaceae, including the genera Fagus, Lithocarpus and Quercus (Neves and Halling 2010, Montoya and Bandala 2011, Zhang and Li 2018. The two Thai Erythrophylloporus species were found in forests dominated by Dipterocarpaceae trees, mainly Dipterocarpus, including D. tuberculatus, D. obtusifolius and Shorea, including S. obtusa and S. siamensis. However, some Quercus and Lithocarpus trees (Fagaceae) were also observed in the vicinity and could also be the ectomycorrhizal partners. Further study is needed to confirm the ectomycorrhizal relationships of Erythrophylloporus.