Filamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process of Fusarium graminearum in wheat spikes by generating a dual weighted gene co-expression network (WGCN). Notably, the network contained a mycotoxin-enriched fungal module (F12) that exhibited a significant correlation with a detoxification gene-enriched wheat module (W12). This correlation in gene expression was validated through quantitative PCR. By examining a fungal module with genes highly expressed during early symptomless infection that was correlated to a wheat module enriched in oxidative stress genes, we identified a gene encoding FgKnr4, a protein containing a Knr4/Smi1 disordered domain. Through comprehensive analysis, we confirmed the pivotal role of FgKnr4 in various biological processes, including oxidative stress tolerance, cell cycle stress tolerance, morphogenesis, growth, and pathogenicity. Further studies confirmed the observed phenotypes are partially due to the involvement of FgKnr4 in regulating the fungal cell wall integrity pathway by modulating the phosphorylation of the MAP-kinase MGV1. Orthologues of the FgKnr4 gene are widespread across the fungal kingdom but are absent in other Eukaryotes, suggesting the protein has potential as a promising intervention target. Encouragingly, the restricted growth and highly reduced virulence phenotypes observed for ΔFgknr4 were replicated upon deletion of the orthologous gene in the wheat fungal pathogen Zymoseptoria tritici. Overall, this study demonstrates the utility of an integrated network-level analytical approach to pinpoint genes of high interest to pathogenesis and disease control.

Filamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process of Fusarium graminearum in wheat spikes by generating a dual weighted gene co-expression network (WGCN). Notably, the network contained a mycotoxin-enriched fungal module that exhibited a significant correlation with a detoxification gene-enriched wheat module. This correlation in gene expression was validated through quantitative PCR. By examining a fungal module with genes highly expressed during early symptomless infection, we identified a gene encoding FgKnr4, a protein containing a Knr4/Smi1 disordered domain. Through comprehensive analysis, we confirmed the pivotal role of FgKnr4 in various biological processes, including morphogenesis, growth, cell wall stress tolerance, and pathogenicity. Further studies confirmed the observed phenotypes are partially due to the involvement of FgKnr4 in regulating the fungal cell wall integrity pathway by modulating the phosphorylation of the MAP-kinase MGV1. Orthologues of FgKnr4 are widespread across the fungal kingdom but are absent in other Eukaryotes, suggesting the protein has potential as a promising intervention target. Encouragingly, the restricted growth and highly reduced virulence phenotypes observed for ΔFgknr4 were replicated upon deletion of the orthologous gene in the wheat fungal pathogen Zymoseptoria tritici . Overall, this study demonstrates the utility of an integrated network-level analytical approach to pinpoint genes of high interest to pathogenesis and disease control. ### Competing Interest Statement The authors have declared no competing interest.

Pneumocystis jirovecii is a major fungal pathogen of humans that infects healthy individuals, colonizing the lungs of infants. In immunocompromised and transplant patients, this fungus causes life-threatening pneumonia, and these Pneumocystis infections remain among the most common and serious infections in HIV/AIDS patients.

Phytopathogenic fungi pose a serious threat to global food security. Next-generation sequencing technologies, such as transcriptomics, are increasingly used to profile infection, assess environmental adaptation and gauge host-responses. The accumulation of these large-scale data has created the opportunity to employ new computational methods to gain greater biological insights. Machine learning approaches, that learn to identify patterns in complex data sets, have recently been applied to the field of plant-pathogen interactions. Here, we apply a machine learning approach to transcriptomics data for the fungal pathogen Zymoseptoria tritici , to predict the onset of infection as measured by timing of the appearance of necrosis. We present a method for identifying the most important genes that predict infection timings, accurately classify isolates as early and late infectors and predict the timing of infection of ‘novel’ isolates using only a subset of the data. These methods and the genes identified further demonstrate the use of these tools in the field of plant-pathogen interactions and have implications for the identification of biomarkers for disease monitoring and forecasting. Fungi that infect plants pose a serious threat to global food security. Methods to study these pathogens generate vast amounts of data that create new opportunities for computational tools to analyse them. Machine learning methods can learn patterns in complex data such as when genes are turned on or off in fungal plant pathogens. In this study we use machine learning approaches to predict the onset of infection in several isolates of an important fungal pathogen. We show that these methods can identify a small group of genes that are predictive of the infection onset. We can even use these methods on ‘novel’ isolates to infer the likely timing of disease development. Our work has implications for plant disease diagnosis, monitoring and forecasting.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition characterized by the loss of motor neurons. We utilized single-cell transcriptomics to uncover dysfunctional pathways in degenerating motor neurons differentiated from SOD1 E100G ALS patient-derived induced pluripotent stem cells (iPSCs) and respective isogenic controls. Differential gene expression and network analysis identified activation of developmental pathways and core transcriptional factors driving the ALS motor neuron gene dysregulation. Specifically, we identified activation of SMAD2, a downstream mediator of the transforming growth factor β (TGF-β) signaling pathway as a key driver of SOD1 iPSC-derived motor neuron degeneration. Importantly, our analysis indicates that activation of TGFβ signaling may be a common mechanism shared between SOD1, FUS, C9ORF72, VCP, and sporadic ALS motor neurons. Our results demonstrate the utility of single-cell transcriptomics in mapping disease-relevant gene regulatory networks driving neurodegeneration in ALS motor neurons. We find that ALS-associated mutant SOD1 targets transcriptional networks that perturb motor neuron homeostasis.

SNIP1 (Smad nuclear interacting protein 1) is a widely expressed transcriptional suppressor of the TGF-β signal-transduction pathway which plays a key role in human spliceosome function. Here, we describe extensive genetic studies and clinical findings of a complex inherited neurodevelopmental disorder in 35 individuals associated with a SNIP1 NM_024700.4:c.1097A>G, p.(Glu366Gly) variant, present at high frequency in the Amish community. The cardinal clinical features of the condition include hypotonia, global developmental delay, intellectual disability, seizures, and a characteristic craniofacial appearance. Our gene transcript studies in affected individuals define altered gene expression profiles of a number of molecules with well-defined neurodevelopmental and neuropathological roles, potentially explaining clinical outcomes. Together these data confirm this SNIP1 gene variant as a cause of an autosomal recessive complex neurodevelopmental disorder and provide important insight into the molecular roles of SNIP1, which likely explain the cardinal clinical outcomes in affected individuals, defining potential therapeutic avenues for future research.

Eccentric (ECC) and concentric (CON) contractions induce distinct muscle remodelling patterns that manifest early during exercise training, the causes of which remain unclear. We examined molecular signatures of early contraction mode-specific muscle adaptation via transcriptome-wide network and secretome analyses during 2 weeks of ECC- versus CON-specific (downhill versus uphill running) exercise training (exercise 'habituation'). Despite habituation attenuating total numbers of exercise-induced genes, functional gene-level profiles of untrained ECC or CON were largely unaltered post-habituation. Network analysis revealed 11 ECC-specific modules, including upregulated extracellular matrix and immune profiles plus downregulated mitochondrial pathways following untrained ECC. Of 3 CON-unique modules, 2 were ribosome-related and downregulated post-habituation. Across training, 376 ECC-specific and 110 CON-specific hub genes were identified, plus 45 predicted transcription factors. Secreted factors were enriched in 3 ECC- and/or CON-responsive modules, with all 3 also being under the predicted transcriptional control of SP1 and KLF4. Of 34 candidate myokine hubs, 1 was also predicted to have elevated expression in skeletal muscle versus other tissues: THBS4, of a secretome-enriched module upregulated after untrained ECC. In conclusion, distinct untrained ECC and CON transcriptional responses are dampened after habituation without substantially shifting molecular functional profiles, providing new mechanistic candidates into contraction-mode specific muscle regulation.

Background Beta cell identity changes occur in the islets of donors with diabetes, but the molecular basis of this remains unclear. Protecting residual functional beta cells from cell identity changes may be beneficial for patients with diabetes. Results A somatostatin-positive cell population was induced in stressed clonal human EndoC-βH1 beta cells and was isolated using FACS. A transcriptomic characterisation of somatostatin-positive cells was then carried out. Gain of somatostatin-positivity was associated with marked dysregulation of the non-coding genome. Very few coding genes were differentially expressed. Potential candidate effector genes were assessed by targeted gene knockdown. Targeted knockdown of the HNRNPD gene induced the emergence of a somatostatin-positive cell population in clonal EndoC-βH1 beta cells comparable with that we have previously reported in stressed cells. Conclusions We report here a role for the HNRNPD gene in determination of beta cell identity in response to cellular stress. These findings widen our understanding of the role of RNA binding proteins and RNA biology in determining cell identity and may be important for protecting remaining beta cell reserve in diabetes.

Abstract Background Skeletal muscle atrophy manifests across numerous diseases; however, the extent of similarities/differences in causal mechanisms between atrophying conditions in unclear. Ageing and disuse represent two of the most prevalent and costly atrophic conditions, with resistance exercise training (RET) being the most effective lifestyle countermeasure. We employed gene‐level and network‐level meta‐analyses to contrast transcriptomic signatures of disuse and RET, plus young and older RET to establish a consensus on the molecular features of, and therapeutic targets against, muscle atrophy in conditions of high socio‐economic relevance. Methods Integrated gene‐level and network‐level meta‐analysis was performed on publicly available microarray data sets generated from young (18–35 years) m. vastus lateralis muscle subjected to disuse (unilateral limb immobilization or bed rest) lasting ≥7 days or RET lasting ≥3 weeks, and resistance‐trained older (≥60 years) muscle. Results Disuse and RET displayed predominantly separate transcriptional responses, and transcripts altered across conditions were mostly unidirectional. However, disuse and RET induced directly inverted expression profiles for mitochondrial function and translation regulation genes, with COX4I1, ENDOG, GOT2, MRPL12, and NDUFV2, the central hub components of altered mitochondrial networks, and ZMYND11, a hub gene of altered translation regulation. A substantial number of genes (n = 140) up‐regulated post‐RET in younger muscle were not similarly up‐regulated in older muscle, with young muscle displaying a more pronounced extracellular matrix (ECM) and immune/inflammatory gene expression response. Both young and older muscle exhibited similar RET‐induced ubiquitination/RNA processing gene signatures with associated PWP1, PSMB1, and RAF1 hub genes. Conclusions Despite limited opposing gene profiles, transcriptional signatures of disuse are not simply the converse of RET. Thus, the mechanisms of unloading cannot be derived from studying muscle loading alone and provides a molecular basis for understanding why RET fails to target all transcriptional features of disuse. Loss of RET‐induced ECM mechanotransduction and inflammatory profiles might also contribute to suboptimal ageing muscle adaptations to RET. Disuse and age‐dependent molecular candidates further establish a framework for understanding and treating disuse/ageing atrophy.

Circular RNAs are non-coding RNA molecules with gene regulatory potential that have been associated with several human diseases. They are stable and present in the circulation, making them excellent candidates for biomarkers of disease. Despite their promise as biomarkers or future therapeutic targets, information on their expression and functionality in human pancreatic islets is a relatively unexplored subject. Here we aimed to produce an enriched circRNAome profile for human pancreatic islets by CircleSeq, and to explore the relationship between circRNA expression, diabetes status, genotype at T2D risk loci and measures of glycaemia (insulin secretory index; SI and HbA1c) in human islet preparations from healthy control donors and donors with type 2 diabetes using ANOVA or linear regression as appropriate. We also assessed the effect of elevated glucose, cytokine and lipid and hypoxia on circRNA expression in the human beta cell line EndoC-βH1. We identified over 2600 circRNAs present in human islets. Of the five most abundant circRNAs in human islets, four (circCIRBP, circZKSCAN, circRPH3AL and circCAMSAP1) demonstrated marked associations with diabetes status. CircCIRBP demonstrated an association with insulin secretory index in isolated human islets and circCIRBP and circRPH3AL displayed altered expression with elevated fatty acid in treated EndoC-βH1 cells. CircCAMSAP1 was also noted to be associated with T2D status in human peripheral blood. No associations between circRNA expression and genotype at T2D risk loci were identified in our samples. Our data suggest that circRNAs are abundantly expressed in human islets, and that some are differentially regulated in the islets of donors with type 2 diabetes. Some islet circRNAs are also expressed in peripheral blood and the expression of one, circCAMSAP1, correlates with diabetes status. These findings highlight the potential of circRNAs as biomarkers for T2D.

Candida albicans is a normal member of the human microbiome. It is also an opportunistic pathogen, which can cause life-threatening systemic infections in severely immunocompromized individuals. Despite the availability of antifungal drugs, mortality rates of systemic infections are high and new drugs are needed to overcome therapeutic challenges including the emergence of drug resistance. Targeting known disease pathways has been suggested as a promising avenue for the development of new antifungals. However, <30% of C. albicans genes are verified with experimental evidence of a gene product, and the full complement of genes involved in important disease processes is currently unknown. Tools to predict the function of partially or uncharacterized genes and generate testable hypotheses will, therefore, help to identify potential targets for new antifungal development. Here, we employ a network-extracted ontology to leverage publicly available transcriptomics data and identify potential candidate genes involved in disease processes. A subset of these genes has been phenotypically screened using available deletion strains and we present preliminary data that one candidate, PEP8, is involved in hyphal development and immune evasion. This work demonstrates the utility of network-extracted ontologies in predicting gene function to generate testable hypotheses that can be applied to pathogenic systems. This could represent a novel first step to identifying targets for new antifungal therapies.

Circular RNAs (circRNAs) are an emerging class of non-coding RNA molecules that are thought to regulate gene expression and human disease. Despite the observation that circRNAs are known to accumulate in older organisms and have been reported in cellular senescence, their role in aging remains relatively unexplored. Here, we have assessed circRNA expression in aging human blood and followed up age-associated circRNA in relation to human aging phenotypes, mammalian longevity as measured by mouse median strain lifespan and cellular senescence in four different primary human cell types. We found that circRNAs circDEF6, circEP300, circFOXO3 and circFNDC3B demonstrate associations with parental longevity or hand grip strength in 306 subjects from the InCHIANTI study of aging, and furthermore, circFOXO3 and circEP300 also demonstrate differential expression in one or more human senescent cell types. Finally, four circRNAs tested showed evidence of conservation in mouse. Expression levels of one of these, circPlekhm1, was nominally associated with lifespan. These data suggest that circRNA may represent a novel class of regulatory RNA involved in the determination of aging phenotypes, which may show future promise as both biomarkers and future therapeutic targets for age-related disease.

Resistance exercise (RE) remains a primary approach for minimising aging muscle decline.Understanding muscle adaptation to individual contractile components of RE (eccentric, concentric) might optimise RE-based intervention strategies.Herein, we employed a network-driven pipeline to identify putative molecular drivers of muscle aging and contraction mode responses.RNA-sequencing data was generated from young (21±1 y) and older (70±1 y) human skeletal muscle before and following acute unilateral concentric and contralateral eccentric contractions.Application of weighted gene co-expression network analysis identified 33 distinct gene clusters ('modules') with an expression profile regulated by aging, contraction and/or linked to muscle strength.These included two contraction 'responsive' modules (related to 'cell adhesion' and 'transcription factor' processes) that also correlated with the magnitude of post-exercise muscle strength decline.Module searches for 'hub' genes and enriched transcription factor binding sites established a refined set of candidate moduleregulatory molecules (536 hub genes and 60 transcription factors) as possible contributors to muscle aging and/or contraction responses.Thus, network-driven analysis can identify new molecular candidates of functional relevance to muscle aging and contraction mode adaptations.

We show that theC. albicansureohydrolases arginase (Car1), agmatinase (Agt1), and guanidinobutyrase (Gbu1) can orchestrate an arginase-independent route for polyamine production and that this is important forC. albicansgrowth and survival in microenvironments of the mammalian host.

Circular RNAs (circRNAs) are an emerging class of non-coding RNA molecules that are thought to regulate gene expression and human disease. Despite the observation that circRNAs are known to accumulate in older organisms and have been reported in cellular senescence, their role in aging remains relatively unexplored. Here, we have assessed circRNA expression in aging human blood and followed up age-associated circRNA in relation to human aging phenotypes, mammalian longevity as measured by mouse median strain lifespan and cellular senescence in four different primary human cell types. We found that circRNAs circDEF6, circEP300, circFOXO3 and circFNDC3B demonstrate associations with parental longevity or hand grip strength in 306 subjects from the InCHIANTI study of aging, and furthermore, circFOXO3 and circEP300 also demonstrate differential expression in one or more human senescent cell types. Finally, four circRNAs tested showed evidence of conservation in mouse. Expression levels of one of these, circPlekhm1, was nominally associated with lifespan. These data suggest that circRNA may represent a novel class of regulatory RNA involved in the determination of aging phenotypes, which may show future promise as both biomarkers and future therapeutic targets for age-related disease.

In the blood stream, arginine is an essential amino acid that is required by phagocytes to synthesize iNOS. Previously we showed that the fungus Candida albicans induces host arginase production that diverts arginine from the pathway that leads to the production of nitrite oxide. We therefore investigated whether C. albicans arginase activity also contributed to the protection of the fungus by competing for arginine during infections. Three C. albicans genes had been annotated as putative arginase encoding genes. Heterologous expression of these genes suggested all three had some arginase activity and one gene product (Car1) encoded a bone fide arginase that was required for growth on arginine. However, single and double mutations in the two other genes (AGM1 and GBU1) did not affect growth on arginine as a single nitrogen source and were found instead to encode agmatinase and guanidinobutyrase respectively that participate in two other pathways related to arginine metabolism. This family of three enzymes therefore exhibits mixed biochemical activities and collectively participate in the catabolism of exogenous and endogenous sources of arginine. Virulence of the triple mutant lacking all three genes was reduced in a Galleria infection model, but single or double mutants were fully virulent. None of the single or multiple mutants affected host NO production suggesting they do not influence the oxidative burst of phagocytes. In addition, CAR1 expression was required for hyphal growth. This family of enzymes therefore represent a novel enzyme set that is essential for growth in vivo and indirectly for fungal virulence.

The rapid acquisition of drug resistance by Candida glabrata has placed an increased burden on health systems. Combination therapies, which apply multiple known compounds, can thwart the compensatory behaviours that lead to drug resistance and can open therapeutic avenues that were not previously available. Genetic interactions, in which the loss of a pair of genes has a stronger effect than the loss of either of the genes alone, can be useful in identifying targets for combination therapy. However, the number of possible interactions is immense while experimentally establishing a genetic interaction is non-trivial. We are developing a method for predicting genetic interactions in C. glabrata as a means to prioritize the experimental validation of interactions and combination therapies. The method applies machine-learning techniques to infer genetic interactions from diverse data in C. glabrata and from other yeast species, such as coexpression, protein-protein interactions and coevolution. We are establishing the method by building a model for Saccharomyces cerevisiae to validate against the large-scale genetic interaction data available for that species. This model will then integrated with C. glabrata-specific data, validated against known genetic interactions, and used to produce novel predictions for further characterisation in the lab.

The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens' motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study.

Optimization of resistance exercise (RE) remains a hotbed of research for muscle building and maintenance. However, the interactions between the contractile components of RE (i.e. concentric (CON) and eccentric (ECC)) and age, are poorly defined. We used transcriptomics to compare age-related molecular responses to acute CON and ECC exercise. Eight young (21±1 y) and eight older (70±1 y) exercise-naïve male volunteers had vastus lateralis biopsies collected at baseline and 5 h post unilateral CON and contralateral ECC exercise. RNA was subjected to next-generation sequencing and differentially expressed (DE) genes tested for pathway enrichment using Gene Ontology (GO). The young transcriptional response to CON and ECC was highly similar and older adults displayed moderate contraction-specific profiles, with no GO enrichment. Age-specific responses to ECC revealed 104 DE genes unique to young, and 170 DE genes in older muscle, with no GO enrichment. Following CON, 15 DE genes were young muscle-specific, whereas older muscle uniquely expressed 147 up-regulated genes enriched for cell adhesion and blood vessel development, and 28 down-regulated genes involved in mitochondrial respiration, amino acid and lipid metabolism. Thus, older age is associated with contraction-specific regulation often without clear functional relevance, perhaps reflecting a degree of stochastic age-related dysregulation.