Biology subjects

Goyal, S.

Publications and source records attributed to Goyal, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Deciphering the Gut-Brain Dialogue: A Survey-Based and In-Silico Comparative Analysis of Gut Microbial Dysbiosis in Common Neurological Disorders

The gut microbiome maintains a complex, bidirectional communication network with the central nervous system, commonly referred to as the gut-brain axis and its disruption has been implicated in several neurological disorders. This study combines a survey-based assessment of public awareness with an in-silico comparative analysis of gut microbial dysbiosis across four prevalent neurological disorders as observed in the current study: depression, anxiety, schizophrenia and autism spectrum disorder (ASD). A structured, anonymous online survey (n = 230) captured perceptions of the gut-brain connection along with dietary, lifestyle and gastrointestinal correlates of stress in a predominantly young, health-sciences-affiliated Indian cohort. In parallel, disorder-specific lists of elevated and reduced faecal microbial taxa were retrieved from the Disbiome database, compared using a multiple list comparator and taxonomically classified using the NCBI Taxonomy tool to construct phylogenetic trees in iTOL. Approximately three-quarters of respondents were aware of a potential gut-mental health link, yet about half reported no specific dietary practice and roughly 60% experienced stress-related digestive symptoms while rarely seeking medical consultation for them. Comparative analysis showed that depression, anxiety and schizophrenia shared a substantially overlapping dysbiosis signature, with common elevation of Actinomyces, Bacteroidaceae, Blautia, Eggerthella, Oscillibacter, Parasutterella and Veillonella and common reduction of Coprococcus, Lachnospiraceae, Ruminococcaceae, Clostridium, Faecalibacterium and Sutterella. In contrast, ASD displayed a distinct microbial signature with limited overlap with the other three disorders. Phylogenetic clustering confirmed that the shared taxa belonged predominantly to the phyla Bacillota (formerly Firmicutes), Bacteroidota (formerly Bacteroidetes), Actinomycetota (formerly Actinobacteria) and Pseudomonadota (formerly Proteobacteria). Notably, this phylum-level pattern parallels recent comparative analyses of microbial dysbiosis in neurodegenerative diseases, suggesting that broad phylogenetic shifts may be a relatively general correlate of chronic neurological disease, while disorder specificity emerges at the level of individual taxa. These findings support a shared microbial pathway linking depression, anxiety and schizophrenia that is distinct from the dysbiosis pattern observed in ASD and they underscore the value of microbiome-informed, disorder-specific therapeutic strategies.

bioinformatics↗

bioRxiv2026

From shielding effect to hierarchical structures: a coarse-grained description of diversity

The shared trade-off in microbial resource-utilization strategies has been proposed to resolve the paradox of the plankton, which states that the diversity observed in nature greatly exceeds the theoretically predicted upper bound that limits the number of coexisting species to the number of available resources. However, three important aspects remain unaddressed in this line of work. First, trade-offs have been quantified not only for phenotypes associated with alternative resource utilization, but also for other modes of microbial interaction. Second, in natural systems, not all taxa are subjected to the same trade-offs. Third, existing trade-off-based models do not explain the empirically observed clustering of taxa according to functional similarity. Here, we extend the trade-off-based framework to incorporate multiple types of resources. We assume that different subsets of taxa are constrained by distinct sets of trade-offs. Under this framework, our model predicts the emergence of clusters: while taxa with similar strategies can belong to the same cluster, each cluster is sustained by taxa with substantially different strategies. The resulting system supports high diversity with an effectively unlimited number of coexisting taxa, yet can still be described as a low-diversity community in which the number of coexisting functional clusters does not exceed the theoretical upper bound.

ecology↗

bioRxiv2026

Molecular characterization of the effector-immunity pair Rhs2-SciX from Salmonella Typhimurium

The type VI secretion system (T6SS) is a dynamic nanomachine used by bacteria to compete for space and nutrients. To kill rival bacteria, the T6SS secretes toxic effector proteins directly into adjacent cells in a contact-dependent manner. Effectors have diverse biochemical functions that arise from subtle structural modifications to related enzyme folds. To protect from self-intoxication, effectors are encoded with a cognate immunity protein in effector-immunity pairs. Immunity proteins inhibit toxicity by directly binding the effector active site and are as structurally diverse as their effectors. Salmonella Typhimurium has several known effectors of diverse biochemical functions, however the effector-immunity pair Rhs2-SciX remains largely unstudied. Here, we take a structural approach and show that Rhs2 is a BECR family nuclease through modeling and toxicity assays. Furthermore, we solve an X-ray crystal structure of SciX and study the solution-state properties of the immunity protein to gain insight into the binding and inhibition mechanism of Rhs2. Finally, we discover that Rhs2 binds directly to EF-Tu suggesting that Rhs2 inhibits translation to cause cell death. Our work probes the structure and function of the effector-immunity pair Rhs2-SciX, demonstrates the biochemical diversity of Salmonella T6SS effectors, and highlights the conserved T6SS toxicity strategy of binding EF-Tu.

biochemistry↗

bioRxiv2026

Domain-Specific Agonist Binding Affinities Explain Structural and Functional Regulation of TRPM2

TRPM2 is a Ca{superscript 2}-permeable cation channel activated by ADP-ribose (ADPR) and oxidative stress, yet the relative contributions of its two nucleotide-binding domains, MHR1/2 and NUDT9H, remain incompletely understood. Here, we quantitatively determine the affinities of the isolated human TRPM2 MHR1/2 and NUDT9H domains for ADPR, 2-deoxy-dADPR (dADPR), and 8-Br-cADPR using biophysical approaches. The MHR1/2 domain binds ADPR with high affinity (Kd {approx} 0.5 {micro}M), whereas the NUDT9H domain displays substantially lower affinity (Kd {approx} 192 {micro}M), revealing a difference of nearly three orders of magnitude. Mutational analysis demonstrates that alterations in MHR1/2 strongly affect ligand binding and channel activation, while mutations within NUDT9H that markedly reduce ligand affinity exert only modest effects on gating. In parallel, we quantify intracellular ADPR concentrations in resting and hydrogen peroxide-stimulated cells and find that they remain well below the affinity required for substantial NUDT9H occupancy. Together, our findings indicate that high-affinity binding to the MHR1/2 domain is sufficient to drive TRPM2 activation under physiological conditions, whereas the NUDT9H domain likely contributes to maintaining the structural integrity of the channel rather than directly mediating ligand-dependent activation. These results provide a quantitative framework for understanding ligand-dependent TRPM2 regulation in cells.

biophysics↗

bioRxiv2026

Transient signaling of free ADP-ribose monitored with an intracellular biosensor

We have developed a biosensor enabling the dynamic, compartmentalized, and longitudinal measurements of intracellular ADP-ribose (ADPR) in live cells. Free ADPR is a critical signaling metabolite derived from nicotinamide adenine dinucleotide (NAD+). As an agonist for Transient Receptor Potential Melastatin 2 (TRPM2), ADPR levels can regulate immune responses during infection, as well as nociception and adjustment of core body temperature. The study of ADPR signaling has been limited, however, by a lack of methods to measure this metabolite in situ. Using the biosensor and its paired non-responsive control, we determine that intracellular ADPR accumulation was transient and tunable. We found that basal concentrations were in the nanomolar range and could be stimulated [~]30-fold to activate TRPM2. We identified that TRPM2 activation, measured by calcium influx, required an intracellular ADPR threshold concentration between 2 - 4 {micro}M at physiological temperature. We observed that the timing of the ADPR rise coincided with TRPM2 activation, thus providing support for ADPR fluctuations being a critically regulated aspect for channel activation. Notably, transient fluctuations of ADPR were not accurately reflected by measurements of intracellular NAD+ loss or calcium levels. Significance StatementWe have developed a unique real-time biosensor for free ADP-ribose that is tuned to physiological concentrations and capable of intracellular measurements in individual cells. Using a calibrated system we determined that concentrations and timing of induced intracellular ADPR aligned with the thermosensitive TRPM2 activity. The data support ADPR as a critical component whose intracellular levels are regulated to control TRPM2 channel opening in cells.

biochemistry↗

bioRxiv2025

Dynamic Regulation of the Immune Repertoire of Bacteria

The CRISPR-Cas system provides adaptive immunity in many bacteria and archaea by storing short fragments of viral DNA, known as spacers, in dedicated genomic arrays. A longstanding question in CRISPR-virus coevolution is the optimal number of spacers for each bacterium to maintain proper phage coverage. In this study, we investigate the optimal CRISPR memory size by combining steady-state immune models with dynamical antigenic traveling wave theory to obtain both analytic and numerical results of coevolutionary dynamics. We focus on two experimentally supported phenomena that shape immune dynamics: primed acquisition, where partial spacer-protospacer matches boost acquisition rates, and cassette expansion, where a short-term increase in memory size drives population dynamics. We find that under primed acquisition, longer optimal arrays benefit from maintaining multiple, partially matching spacers. In contrast, dynamic cassette expansion favors shorter arrays by amplifying the fitness advantage of acquiring a few highly effective new spacers. Together, our results highlight that memory optimality is not fixed, but instead shaped by the interaction of acquisition dynamics and population-level immune pressures.

biophysics↗

bioRxiv2024

Neuroimmune mechanisms of a mouse model of chronic back pain

Chronic back pain (CBP) is the leading cause of disability affecting 1 in 10 people worldwide. Symptoms are marked by persistent lower back pain, reduced mobility, and heightened cold sensitivity. Here, we utilize a mouse model of CBP induced by injecting urokinase-type plasminogen activator (uPA), a proinflammatory agent in the fibrinolytic pathway, between the L2/L3 lumbar vertebrae. We identified neuroimmune interactions contributing to uPA-induced CBP (henceforth, uPA-CBP) in mouse dorsal root ganglia (DRG), where nociceptive neurons reside. Flow cytometric data reveal that uPA-CBP increases CD45+CD11b+ cells in the DRG, a population characteristically implicated in other chronic pain models1. Blocking colony stimulating factor 1 receptor (CSF1R) signaling using PLX5622 partially reduced pain, suggesting CD45+CD11b+ macrophage involvement. Whole-cell patch-clamp electrophysiology data indicated DRG neuron hyperexcitability in CBP mice compared to controls. RNA sequencing revealed upregulation of pain- and inflammation-related genes involved in leukocyte migration. Together, these findings underscore the importance of the DRG neuroimmune axis in mediating chronic back pain. HighlightsO_LIuPA-CBP induces gait changes, mechanical and thermal sensitivity compared to shams C_LIO_LIuPA-CBP mice show increased CD45+CD11b+ cells in DRG compared to shams C_LIO_LIuPA-CBP mice show neuronal excitability in DRG neurons compared to shams C_LIO_LIPain behaviors are alleviated by pharmacologically blocking CSF1R signaling C_LIO_LIDysregulation of inflammation- and ion channel-related genes in uPA-CBP DRG C_LI

neuroscience↗

bioRxiv2024

Polyphosphate Discriminates Protein Conformational Ensembles More Efficiently than DNA Promoting Diverse Assembly and Maturation Behaviors

Disordered proteins and domains often assemble into condensates with polyanionic nucleic acids, primarily via charge complementarity, regulating numerous cellular functions. However, the assembly mechanisms associated with the other abundant and ubiquitous, anionic, stress-response regulating polymer, polyphosphate (polyP), is less understood. Here, we employ the intrinsically disordered DNA binding domain (DBD) of cytidine repressor (CytR) from E.coli to study the nature of assembly processes with polyP and DNA. CytR forms metastable liquid-like condensates with polyP and DNA, while undergoing liquid-to-solid transition in the former and dissolving in the latter. On mutationally engineering the ensemble to exhibit more or less structure and dimensions than the WT, the assembly process with polyP is directed to either condensates with partial time-dependent dissolution or spontaneous aggregation, respectively. On the other hand, the CytR variants form only liquid-like but metastable droplets with DNA which dissolve within a few hours. Polyphosphate induces large secondary-structure changes, with two of the mutants adopting polyproline II-like structures within droplets, while DNA has only minimal structural effects. Our findings reveal how polyphosphate can more efficiently discern conformational heterogeneity in the starting protein ensemble, its structure, and compactness, with broad implications in assembly mechanisms involving polyP and stress response in bacterial systems.

biophysics↗

bioRxiv2024

Oligomerization-Mediated Phase-Separation in the Nucleoid-Associated Sensory Protein H-NS is Controlled by Ambient Cues

H-NS, a nucleoid-associated protein (NAP) from enterobacteria, regulates gene expression by dynamically transducing environmental cues to conformational assembly and DNA binding. In this work, we show that H-NS from Escherichia coli, which can assemble into octameric and tetrameric oligomerization states, forms spontaneous micron-sized liquid-like condensates with DNA at sub-physiological concentrations in vitro. The heterotypic condensates are metastable at 298 K, partially solubilizing with time, while still retaining their liquid-like properties. The condensates display UCST-like phase behavior solubilizing at higher temperatures, but with a large decrease in droplet-assembly propensities at 310 K and also at higher ionic strength. Condensate formation can be tuned in a cyclic manner between 298 and 310 K with the extent of reversibility determined by the incubation time, highlighting strong hysteresis. An engineered phospho-mimetic variant (Y61E) of H-NS, which is dimeric and only weakly binds DNA, is unable to form condensates. The Y61E mutant solubilizes pre-formed H-NS condensates with DNA in a few minutes with nearly an order of magnitude speed-up in droplet dissolution at 310 K relative to 298 K, demonstrating rapid molecular transport between dilute and condensed phases. Our results establish that the oligomerization of H-NS is intrinsically tied not only to DNA binding but also its phase-separation tendencies, while showcasing the regulatable and programmable nature of heterotypic condensates formed by an archetypal NAP via multiple cues and their lifetimes.

biophysics↗

bioRxiv2024

NLRP1B allele 2 does not respond to Val-boro-Pro (VbP) in the intestinal epithelium

The intestinal mucosa must balance tolerance to commensal microbes and luminal antigens with rapid detection of enteric pathogens in order to maintain homeostasis. This balance is facilitated through the regulation of epithelial layer integrity by innate immune receptors. Certain NOD-like receptors (NLRs) expressed in intestinal epithelial cells, including NLRC4 and NLRP9B, form inflammasomes that protect against pathogens by activating caspase-1 to cause extrusion of infected cells. NLRP1B is a murine NLR encoded by five alleles of a highly polymorphic gene homologous to human NLRP1. NLRP1B forms inflammasomes in response to a variety of pathogens that cause intestinal infections, but it has almost exclusively been studied in immune cells and has not been characterized in cells of the intestinal epithelium. Here, we show that Nlrp1b is expressed in ileal and colonic organoids derived for C57BL/6J mice. Nlrp1b was upregulated by interleukin-13 in organoids and by the protozoan Tritrichomonas muris in vivo, suggesting that NLRP1B may be involved in defense against enteric parasites. Surprisingly, while Val-boro-Pro (VbP) activated NLRP1B in bone marrow-derived macrophages, it did not activate NLRP1B in organoids. We furthermore did not detect Nlrp1b in organoids derived from Balb/cJ mice, which express a different allele than the one expressed in C57BL/6J mice. Together, our results suggest that NLRP1B may have an allele-dependent function in murine IECs whose regulation is distinct from that of macrophages.

immunology↗

bioRxiv2024

Machine learning elucidates electrophysiological properties predictive of multi- and single-firing human and mouse dorsal root ganglia neurons

Human and mouse dorsal root ganglia (hDRG and mDRG) neurons are important tools in understanding the molecular and electrophysiological mechanisms that underlie nociception and drive pain behaviors. One of the simplest differences in firing phenotypes is that neurons are single-firing (exhibit only one action potential) or multi-firing (exhibit 2 or more action potentials). To determine if single- and multi-firing hDRG exhibit differences in intrinsic properties, firing phenotypes, and AP waveform properties, and if these properties could be used to predict multi-firing, we measured 22 electrophysiological properties by whole-cell patch-clamp electrophysiology of 94 hDRG neurons from 6 male and 4 female donors. We then analyzed the data using several machine learning models to determine if these properties could be used to predict multi-firing. We used 1000 iterations of Monte Carlo Cross Validation to split the data into different train and test sets and tested the Logistic Regression, k-Nearest Neighbors, Random Forest, Supported Vector Classification, and XGBoost machine learning models. All models tested had a greater than 80% accuracy on average, with Supported Vector Classification and XGBoost performing the best. We found that several properties correlated with multi-firing hDRG neurons and together could be used to predict multi-firing neurons in hDRG including a long decay time, a low rheobase, and long first spike latency. We also found that the hDRG models were able to predict multi-firing with 90% accuracy in mDRG. Targeting the neuronal properties that lead to multi-firing could elucidate better targets for treatment of chronic pain.

neuroscience↗

bioRxiv2024

Improved accuracy for estrous cycle staging using supervised object detection

The estrous cycle regulates reproductive events and hormone changes in female mammals and is analogous to the menstrual cycle in humans. Monitoring this cycle is necessary as it serves as a biomarker for overall health and is crucial for interpreting study results. The estrous cycle comprises four stages influenced by fluctuating levels of hormones, mainly estradiol and progesterone. Tracking the cycle traditionally relies on vaginal cytology, which categorizes stages based on three epithelial cell concentrations. However, this method has limitations, including time-consuming training and variable accuracy among researchers. To address these challenges, this study assessed the feasibility and reliability of two machine learning methods. An object detection-based machine learning model, Object Detection Estrous Staging (ODES), was employed to identify cell types throughout the estrous cycle in mice. A dataset of 555 vaginal cytology images with four different stains was annotated, with 335 images for training, 45 for validation, and 175 for testing. A novel, accurate set of rules for classification was derived by analyzing training images. ODES achieved an average accuracy of 87% in classifying cycle stages and took only 3.9 minutes to analyze 175 test images. The use of object detection machine learning significantly improved accuracy and efficiency compared to previously derived supervised image classification models (33-45% accuracy) and human accuracy (66% accuracy), refining research practices for female studies. These findings facilitate the integration of the estrous cycle into research, enhancing the quality of scientific results by allowing for efficient and accurate identification of the cycle stage.

animal behavior and cognition↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2024

Bacterial ADP-heptose initiates a revival stem cell program in the intestinal epithelium

The intestinal epithelium has an exceptional capacity to repair following injury, and recent evidence has suggested that YAP-dependent signaling was crucial for the expansion of Clu+ revival stem cells (revSCs) with fetal-like characteristics, which are essential for epithelial regeneration. However, neither the mechanism underlying where these revSCs emerge from nor the nature of the physiological cues that induce this revSC program, are clearly identified. Here, we first demonstrate that Alpk1 and Tifa, which encode the proteins essential for the detection of the bacterial metabolite ADP-heptose (ADP-Hep), were expressed by the stem cell pool in the intestinal epithelium. Treatment of intestinal organoids with ADP-Hep not only induced acute NF-{kappa}B pro-inflammatory signaling but also TNF-dependent apoptosis within the crypt, causing blunted proliferation and acute disruption of the crypt architecture, while also triggering induction of a revSC program. To identify the molecular underpinnings of this process, we performed single-cell RNA-seq analysis of ADP-Hep-treated organoids as well as lineage-tracing experiments. Our data reveal that ADP-Hep induced the specific ablation of the homeostatic intestinal stem cell (ISC) pool. Removal of ADP-Hep resulted in the rapid recovery of ISCs through dedifferentiation of Paneth cells, which transiently acquired revSC features and expressed nuclear YAP. Moreover, lineage tracing from Lyz1+ Paneth cells showed that ADP-Hep triggered Paneth cell de-differentiation towards pluripotent and proliferative cells in organoids. In vivo, revSC emergence in response to irradiation-induced injury was severely blunted in Tifa-deficient mice, suggesting that efficient epithelial regeneration in this model required detection of microbiota-derived ADP-Hep by the ALPK1-TIFA pathway. Together, our work reveals that Paneth cells can serve as the cell of origin for revSC induction in the physiological context of microbial stimulation, and that the transient loss of Alpk1-expressing ISCs is the initiating event for this regenerative process.

cell biology↗

bioRxiv2023

Electrophysiological analyses of human dorsal root ganglia and human induced pluripotent stem cell-derived sensory neurons from male and female donors

Human induced pluripotent stem cell-derived sensory neurons (hiPSC-SNs) and human dorsal root ganglia (hDRG) neurons are popular tools in the field of pain research; however, few groups make use of both approaches. For screening and analgesic validation purposes, important characterizations can be determined of the similarities and differences between hDRG and hiPSC-SNs. This study focuses specifically on electrophysiology properties of hDRG in comparison to hiPSC-SNs. We also compared hDRG and hiPSC-SNs from both male and female donors to evaluate potential sex differences. We recorded neuronal size, rheobase, resting membrane potential, input resistance, and action potential waveform properties from 83 hiPSCs-SNs (2 donors) and 108 hDRG neurons (9 donors). We observed several statistically significant electrophysiological differences between hDRG and hiPSC-SNs, such as size, rheobase, input resistance, and several actional potential (AP) waveform properties. Correlation analysis also revealed many properties that were positively or negatively correlated, some of which were differentially correlated between hDRG and hiPSC-SNs. This study shows several differences between hDRG and hiPSC-SNs and allows better understanding of the advantages and disadvantages of both for use in pain research. We hope this study will be a valuable resource for pain researchers considering the use of these human in vitro systems for mechanistic studies and/or drug development projects.

neuroscience↗

bioRxiv2023

Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity.

While animal models have provided key insights into conserved mechanisms of how the lung forms during development, human-specific developmental mechanisms are not always captured. To fully appreciate how developmental defects and disease states alter the function of the lungs, studies in human lung models are important. Here, we sequenced >150,000 single single-cells from 19 healthy human fetal lung tissues from gestational weeks 10-19 and identified at least 58 unique cell types/states contributing to the developing lung. We captured novel dynamic developmental trajectories from various progenitor cells that give rise to club, ciliated, and pulmonary neuroendocrine cells. We also identified four CFTR-expressing progenitor cell types and pinpointed the temporal emergence of these cell types. These developmental dynamics reveal broader epithelial cell plasticity and novel lineage hierarchies that were not previously reported. Combined with spatial transcriptomics, we identified both cell autonomous and non-cell autonomous signalling pathways that may dictate the temporal and spatial emergence of cell lineages. Finally, we showed that human pluripotent stem cell-derived fetal lung models capture cell lineage trajectories specifically through CFTR-expressing progenitor cells, that were also observed in the native fetal tissue. Overall, this study provides a comprehensive single-cell atlas of the developing human lung, outlining the temporal and spatial complexities of cell lineage development. HighlightsO_LISingle-cell transcriptomics atlas from 19 human fetal lungs reveals cellular heterogeneity and previously unappreciated cellular plasticity in the epithelial compartment. C_LIO_LIIdentification of novel CFTR-expressing progenitor cells that gives rise to club, ciliated and PNEC. C_LIO_LINovel RNA velocity facilitated the identification of dynamic lineage trajectories in the epithelial compartment. C_LIO_LITemporally regulated cell signaling through promiscuous interactions between sender and receiving cells may dictate cell lineage fates. C_LIO_LIIntegration of human pluripotent stem cell (hPSC)-derived fetal lung cells and organoids with primary lung dataset show hPSC-differentiations captures key developmental trajectories of fetal epithelial cell states. C_LI

developmental biology↗

bioRxiv2023

Machine Learning-Driven Phenotype Predictions based on Genome Annotations

Over the past two decades, there has been a remarkable and exponential expansion in the availability of genome sequences, encompassing a vast number of isolate genomes, amounting to hundreds of thousands, and now extending to millions of metagenome-assembled genomes. The rapid and accurate interpretation of this data, along with the profiling of diverse phenotypes such as respiration type, antimicrobial resistance, or carbon utilization, is essential for a wide range of medical and research applications. Here, we leverage sequenced-based functional annotations obtained from the RAST annotation algorithm as predictors and employ six machine learning algorithms (K-Nearest Neighbors, Gaussian Naive Bayes, Support Vector Machines, Neural Networks, Logistic Regression, and Decision Trees) to generate classifiers that can accurately predict phenotypes of unclassified bacterial organisms. We apply this approach in two case studies focused on respiration types (aerobic, anaerobic, and facultative anaerobic) and Gram-stain types (Gram negative and Gram positive). We demonstrate that all six classifiers accurately classify the phenotypes of Gram stain and respiration type, and discuss the biological significance of the predicted outcomes. We also present four new applications that have been deployed in The Department of Energy Systems Biology Knowledgebase (KBase) that enable users to: (i) Upload high-quality data to train classifiers; (ii) Annotate genomes in the training set with the RAST annotation algorithm; (iii) Build six different genome classifiers; and (iv) Predict the phenotype of unclassified genomes. (https://narrative.kbase.us/#catalog/modules/kb_genomeclassification)

systems biology↗

bioRxiv2023

Harnessing genetic variations improving seedling vigor for successful crop establishment in deep sown direct-seeded rice

Improving seedling vigour remains key objective for breeders working with direct-seeded rice (DSR). To understand the genetic control of seedling vigour in deep sown DSR, combined genome-wide association mapping, linkage mapping, fine mapping, RNA-sequencing to identify candidate genes and validation of putative candidate genes was performed. Significant phenotypic variations were observed among genotypes in both F3:4:5 and BC2F2:3 populations. The mesocotyl length showed significant positive correlation with %germination, root and shoot length. The 3.79 Mb region on chromosome 7 reported to be associated with mesocotyl elongation. RNA-seq data and RT-PCR results identified and validated seven potential candidate genes. The potential candidate gene, LOC_Os07g25150 codes for Myb-30-related transcription factor. The LOC_Os07g25150 codes for Myb 30-related transcription factor, LOC_Os07g17689 annotated as protein translation factor, LOC_Os07g17770 as tryptophanyl-tRNA synthetase, LOC_Os07g15440 as alanyl-tRNA synthetase family protein, LOC_Os07g24100 as retrotransposon protein and the remaining others as expressed proteins. The antagonistic relationship between Myb-30 and ethylene-mediated signalling (EIN-3) in regulating mesocotyl elongation have been observed. The functional characterization and knocking of LOC_Os07g25150 codes for Myb 30-related transcription factor may provide better understanding of the mechanism behind mesocotyl elongation. The four promising introgression lines with longer mesocotyl length, longer root length and semi-dwarf plant height have been identified.

genomics↗