Biology subjects

Khan, S.

Publications and source records attributed to Khan, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2022

Modelling the role of contour integration in visual inference

Under difficult viewing conditions, the brains visual system uses a variety of recurrent modulatory mechanisms to augment feed-forward processing. One resulting phenomenon is contour integration, which occurs in the primary visual (V1) cortex and strengthens neural responses to edges if they belong to a larger smooth contour. Computational models have contributed to an understanding of the circuit mechanisms of contour integration, but less is known about its role in visual perception. To address this gap, we embedded a biologically grounded model of contour integration in a task-driven artificial neural network, and trained it using a gradient-descent variant. We used this model to explore how brain-like contour integration may be optimized for high-level visual objectives as well as its potential roles in perception. When the model was trained to detect contours in a background of random edges, a task commonly used to examine contour integration in the brain, it closely mirrored the brain in terms of behavior, neural responses, and lateral connection patterns. When trained on natural images, the model enhanced weaker contours and distinguished whether two points lay on the same vs. different contours. The model learnt robust features that generalized well to out-of-training-distribution stimuli. Surprisingly, and in contrast with the synthetic task, a parameter-matched control network without recurrence performed the same or better than the model on the natural-image tasks. Thus a contour integration mechanism is not essential to perform these more naturalistic contour-related tasks. Finally, the best performance in all tasks was achieved by a modified contour integration model that did not distinguish between excitatory and inhibitory neurons. Author summaryDeep networks are machine-learning systems that consist of interconnected neuron-like elements. More than other kinds of artificial system, they rival human information processing in a variety of tasks. These structural and functional parallels have raised interest in using deep networks as simplified models of the brain, to better understand of brain function. For example, incorporating additional biological phenomena into deep networks may help to clarify how they affect brain function. In this direction, we adapted a deep network to incorporate a model of visual contour integration, a process in the brain that makes contours appear more visually prominent. We found that suitable training led this model to behave much like the corresponding brain circuits. We then investigated potential roles of the contour integration mechanism in processing of natural images, an important question that has been difficult to answer. The results were not straightforward. For example, the contour integration mechanism actually impaired the networks ability to tell whether two points lay on the same contour or not, but improved the networks ability to generalize this skill to a different group of images. Overall, this approach has raised more sophisticated questions about the role of contour integration in natural vision.

neuroscience↗

bioRxiv2022

Multigenerational effect of heat stress on the Drosophila melanogaster sperm proteome

The notion that genes are the sole units of heredity and that a barrier exists between soma and germline has been a major hurdle in elucidating the heritability of traits that were observed to follow a non-Mendelian inheritance pattern. It was only after the conception of epigenetics by Conrad Waddington that the effect of parental environment on subsequent generations via non-DNA sequence-based mechanisms, such as DNA methylation, chromatin modifications, non-coding RNAs and proteins, could be established, now referred to as multigenerational epigenetic inheritance. Despite growing evidence, the male gamete-derived epigenetic factors that mediate the transmission of such phenotypes are seldom explored, particularly in the model organism Drosophila melanogaster. Using the heat stress-induced multigenerational epigenetic inheritance paradigm in a widely used position-effect variegation line of Drosophila, named white-mottled, we have dissected the effect of heat stress on the sperm proteome in the current study. We demonstrate that multiple successive generations of heat stress at the early embryonic stage results in a significant downregulation of proteins associated with a diverse set of functions, such as translation, chromatin organization, microtubule-based processes, and generation of metabolites and energy, in the sperms. Based on our findings, we propose chromatin-based epigenetic mechanisms, a well-established mechanism for multigenerational effects, as a plausible way of transmitting heat stress memory via the male germline in this case. Moreover, we show that despite these heat stress-induced changes, the life-history traits, such as reproductive fitness and stress tolerance of the subsequent generations, are unaffected, probing the evolutionary relevance of multigenerational epigenetic effects.

developmental biology↗

bioRxiv2022

Rad51 inhibition sensitizes non-replicating quiescent cells to UVB radiation and transcription stress

DNA damage induced by environmental, occupational, and chemotherapeutic compounds lead to a variety of cellular responses that are potentially impacted by the proliferation status of the cell. Using small molecule inhibitors of various DNA doublestrand break (DSB) repair pathways in non-replicating, quiescent human cells exposed to UVB radiation, we unexpectedly observed a major role for the recombination protein Rad51 in promoting cell survival. In contrast to a previous report indicating a requirement for nucleotide excision repair (NER) in DSB formation after UV exposure in quiescent cells, we observed DSB formation and Rad51 function to be independent of NER. Moreover, our analyses of DNA damage response kinase signaling in quiescent cells identified protein substrates that were either dependent or independent of both NER and apoptotic signaling. Finally, we observed that Rad51 inhibition sensitized nonreplicating quiescent cells to diverse genotoxic stressors, including those inducing DNA- RNA hybrids and inhibiting transcription. Thus, these findings clarify the mechanisms by which DSBs arise in non-replicating cells and highlight the important role of Rad51 in promoting quiescent cell survival in response to general genotoxic stress. Summary statementDNA double strand breaks are generated independent of nucleotide excision repair in UV-irradiated quiescent cells and require the recombination protein Rad51 to promote cell survival.

cell biology↗

bioRxiv2022

Psychosis-associated Valine to Leucine mutation in Neuregulin1 disrupts expression of a schizophrenia susceptibility gene network within the hippocampus and alters adult hippocampal neurogenesis.

Neuregulin1 (Nrg1) signaling is critical for aspects of neuronal development and function from fate specification to synaptic plasticity. Type III Nrg1 is a synaptic protein which engages in bi-directional signaling with its receptor ErbB4. Forward signaling engages ErbB4 phosphorylation, whereas back signaling engages two known mechanisms: 1. local axonal PI3K-AKT signaling, and 2. cleavage by gamma secretase resulting in cytosolic release of the intracellular domain (ICD), which can traffic to the nucleus (Bao, Wolpowitz et al. 2003, Hancock, Canetta et al. 2008). To dissect the contribution of these alternate signaling strategies to neuronal development we generated a transgenic mouse with a missense mutation (V321L) in the Nrg1 transmembrane domain that disrupts nuclear back signaling with minimal effects on forward signaling or local back-signaling and was previously found to be associated with psychosis (Walss-Bass, Liu et al. 2006). We combined RNA sequencing, retroviral fate mapping of neural stem cells, behavioral analyses, and various network analyses of transcriptomic data to investigate the effect of disrupting Nrg1 nuclear back-signaling in the dentate gyrus (DG) of male and female mice. The V321L mutation impairs nuclear translocation of the Nrg1 ICD and alters gene expression in the DG. V321L mice show reduced stem cell proliferation, altered cell cycle dynamics, fate specification defects, and dendritic dysmorphogenesis. Orthologs of known schizophrenia (SCZ)-susceptibility genes were dysregulated in the V321L DG. These genes coordinated a larger network with other dysregulated genes. WGCNA and protein-interaction network analyses revealed striking similarity between DG transcriptomes of V321L mouse and humans with schizophrenia. SIGNIFICANCE STATEMENTSynaptic contact is predicted to be a regulator of the generation of nuclear signaling by Nrg1. Here we show that a schizophrenia-associated mutation in Nrg1 disrupts its ability to communicate extracellular signals to the neuronal genome which results in altered expression of a gene network enriched for orthologs of schizophrenia-susceptibility genes. The striking overlap in functional and molecular alterations between a single rare homozygous missense mutation (V321L) and schizophrenia patient data (complex polygenic and environmental burden) underscores potential convergence of rare and common variants on the same cellular and molecular phenotypes. Furthermore, our data indicate that the evolutionarily conserved gene networks that form the basis for this risk are necessary for coordinating neurodevelopmental events in the DG.

neuroscience↗

bioRxiv2022

CanSeer: A Method for Development and Clinical Translation of Personalized Cancer Therapeutics

Computational modeling and analysis of biomolecular network models annotated with cancer patient-specific multi-omics data can enable the development of personalized therapies. Current endeavors aimed at employing in silico models towards personalized cancer therapeutics remain to be fully translated. In this work, we present "CanSeer" a novel multi-stage methodology for developing in silico models towards clinical translation of personalized cancer therapeutics. The proposed methodology integrates state-of-the-art dynamical analysis of biomolecular network models with patient-specific genomic and transcriptomic data to assess the individualized therapeutic responses to targeted drugs and their combinations. CanSeers translational approach employs transcriptomic data (RNA-seq based gene expressions) with genomic profile (CNVs, SMs, and SVs). Specifically, patient-specific cancer driver genes are identified, followed by the selection of druggable and/or clinically actionable targets for therapeutic interventions. To exemplify CanSeer, we have designed three case studies including (i) lung squamous cell carcinoma, (ii) breast invasive carcinoma, and (iii) ovarian serous cystadenocarcinoma. The case study on lung squamous cell carcinoma concluded that restoration of Tp53 activity together with an inhibition of EGFR as an efficacious combinatorial treatment for patients with Tp53 and EGFR cancer driver genes. The findings from the cancer case study helped identify personalized treatments including APR-246, APR-246+palbociclib, APR-246+osimertinib, APR-246+afatinib, APR-246+osimertinib+dinaciclib, and APR-246+afatinib+dinaciclib. The second case study on breast invasive carcinoma revealed CanSeers potential to elucidate drug resistance against targeted drugs and their combinations including KU-55933, afuresertib, ipatasertib, and KU-55933+afuresertib. Lastly, the ovarian cancer case study revealed the combinatorial efficacy of APR-246+carmustine, and APR-246+dinaciclib for treating ovarian serous cystadenocarcinoma. Taken together, CanSeer outlines a novel method for systematic identification of optimal tailored treatments with mechanistic insights into patient-to-patient variability of therapeutic response, drug resistance mechanism, and cytotoxicity profiling towards personalized medicine.

systems biology↗

bioRxiv2022

Cortical dynamics following real-time MEG neurofeedback training of the speed of shifting spatial attention: a pilot study

Neurofeedback is a technique that directs self-regulated modulation of neural activity. This is achieved by delivering real-time feedback derived from brain signals. In our previous work, we introduced a novel method, state-based neurofeedback (sb-NFB) that targets patterns of MEG signals related to shifts in spatial attention. In this pilot study, we used sb-NFB to train participants to decrease the time required to covertly shift spatial attention from one visual hemifield to the other. We characterized the changes to cortical connectivity during each training session. In addition, we run a separate, Posner-like validation task before the training sessions and after the training was complete. We found a significant main effect of training on the reaction time linked to switching spatial attention in both the training task and the validation task. This indicates the achieved improvement in shifting spatial attention generalized to another situation requiring this capability.

neuroscience↗

bioRxiv2022

Inhibition of Aromatase by Hops, Licorice Species, and their bioactive compounds in Postmenopausal Breast Tissue

Breast cancer risk continues to rise post menopause. Endocrine therapies are employed to prevent postmenopausal breast cancer in high-risk women. However, their adverse effects have reduced acceptability and overall success in cancer preventionatural products such as hops (Humulus lupulus) and pharmacopoeial licorice (Glycyrrhiza) species, which are used for managing menopausal symptoms, have demonstrated estrogenic and chemopreventive properties. Their beneficial effects on aromatase activity and expression as important factors in postmenopausal breast carcinogenesis are understudied. The presented data show that Gycyrrhiza inflata (GI) has the highest aromatase inhibition potency among these plants. Moreover, phytoestrogens such as 8-prenylnaringenin from hops as well as liquiritigenin and 8-prenylapigenin from licorice are shown to be potent bioactives, in line with computational docking studies. 8-Prenylnaringenin, GI extract, liquiritigenin, and licochalcone A all suppress aromatase expression in postmenopausal womens breast tissue. Collectively, these data suggest that these natural products may have breast cancer prevention potential for high-risk postmenopausal women.

pharmacology and toxicology↗

bioRxiv2022

scAEGAN: Unification of Single-Cell Genomics Data by Adversarial Learning of Latent Space Correspondences

Recent progress in Single-Cell Genomics have produced different library protocols and techniques for profiling of one or more data modalities in individual cells. Machine learning methods have separately addressed specific integration challenges (libraries, samples, paired-unpaired data modalities). We formulate an unifying data-driven methodology addressing all these challenges. To this end, we design a hybrid architecture using an autoencoder (AE) network together with adversarial learning by a cycleGAN (cGAN) network, jointly referred to as scAEGAN. The AE learns a low-dimensional embedding of each condition, whereas the cGAN learns a non-linear mapping between the AE representations. The core insight is that the AE respects each samples uniqueness, whereas the cGAN exploits the distributional data similarity in the latent space. We evaluate scAEGAN using simulated data and real datasets of a single-modality (scRNA-seq), different library preparations (Fluidigm C1, CelSeq, CelSeq2, SmartSeq), and several data modalities such as paired scRNA-seq and scATAC-seq. We find that scAEGAN outperforms Seurat3 in library integration, is more robust against data sparsity, and beats Seurat 4 in integrating paired data from the same cell. Furthermore, in predicting one data modality from another, scAEGAN outperforms Babel. We conclude scAEGAN surpasses current state-of-the-art methods across several seemingly different integration challenges.

bioinformatics↗

bioRxiv2022

In vitro and in vivo antioxidant therapeutic evaluation of Dodonaea viscosa Jacq.

ContextNatural antioxidants are vital to promote health and treat critical diseased conditions in the modern healthcare system. ObjectiveThis work adds to the index of natural medicines by exploring the antioxidant potential of Dodonaea viscosa Jacq. (Plant-DV). Material and methodsThe aqueous extract of leaves and seeds from plant-DV in freshly prepared phosphate buffer is evaluated for antioxidant potential. In vitro antioxidant potential of the nascent and oxidatively stressed extracts was analyzed through glutathione (GSH) assay, hydrogen peroxide (H2O2) scavenging effect, glutathione-S-transferase (GST) assay, and catalase (CAT) activity. In vivo therapeutic assessment is performed in Wistar Albino rats using vitamin C as a positive control. The livers and kidneys of individual animals are probed for glutathione, glutathione-S-transferase, and catalase activities. ResultsSeeds have GSH contents (59.61 {micro}M) and leaves (32.87 {micro}M) in the fresh aqueous extracts. The hydrogen peroxide scavenging effect of leaves is superior to seeds with 17.25% and 14.18% respectively after 30 min incubation. However, oxidatively stressed extracts with AgI and HgII show declining GSH and GST levels. The plant extracts are non-toxic in rats at 5000 mg/Kg body weight. Liver and kidneys homogenate reveal an increase in GSH, GST, and CAT levels after treatment with 150 {+/-} 2 mg/kg and 300 {+/-} 2 mg/kg body weight plant extract compared with normal saline-treated negative and vitamin C treated positive control. Discussion and ConclusionThe crude aqueous extracts of leaves and seeds of plant DV show promising antioxidant potential both in in vitro and in vivo evaluation.

plant biology↗

bioRxiv2022

A cobB like protein in Oryza sativa indica regulates the mitochondrial machinery under stress conditions

Sirtuins are ubiquitous in nature and are known to play an important role as metabolic regulators. In plants, these NAD+ dependent deacetylases are not well characterized. In this study, we are reporting a new member of sirtuin in Oryza sativa indica. It shares approx. 89% sequence identity with bacterial sirtuin, a class III sirtuin member. This protein is mostly present in mitochondria with trace amounts in the nucleus. It can physically interact with histones H3 and H4 and can specifically deacetylate histone H3 at K9 and K18 positions. In mitochondria, acetyl coA synthetase (AcS) and isocitrate dehydrogenase (IDH2) are the targets for its deacetylation. This removal of acetyl group is the mode of regulation under certain stress conditions. Thus, this is the first mitochondrial cobB targeting important plant machinery under changing growth environment. The OscobB deacetylase activity is not majorly affected by its products, NAM & ADP ribose but are sensitive to certain metal ions like Fe2+ and Mg2+. In contrast to some class III members, it does not have any ADP ribosyl transferase activity. In response to abiotic stress conditions like dehydration and low temperature, this enzyme can also mobilize to the nucleus to regulate the plant metabolism. HighlightsO_LIA new class III member of the sirtuin family found in Oryza sativa indica. C_LIO_LIUnder normal conditions, this protein is localized mostly in mitochondria, with trace amounts in the nucleus. C_LIO_LIThis enzyme is capable of using both NAD+ and NADP+ as a substrate for catalysis. C_LIO_LIIt specifically deacetylates the nuclear histone H3 at K9 and K18 positions. C_LIO_LIMitochondrial proteins acetyl coA synthetase (AcS) and isocitrate dehydrogenase (IDH2) are the regulatory targets of OscobB. C_LIO_LIUnder certain stress conditions in plants like dehydration, pathogenesis and low temperature, there is localisation of OscobB from mitochondria to nucleus. C_LI

plant biology↗

bioRxiv2022

Multimodal single cell data integration challenge: results and lessons learned

Biology has become a data-intensive science. Recent technological advances in single-cell genomics have enabled the measurement of multiple facets of cellular state, producing datasets with millions of single-cell observations. While these data hold great promise for understanding molecular mechanisms in health and disease, analysis challenges arising from sparsity, technical and biological variability, and high dimensionality of the data hinder the derivation of such mechanistic insights. To promote the innovation of algorithms for analysis of multimodal single-cell data, we organized a competition at NeurIPS 2021 applying the Common Task Framework to multimodal single-cell data integration. For this competition we generated the first multimodal benchmarking dataset for single-cell biology and defined three tasks in this domain: prediction of missing modalities, aligning modalities, and learning a joint representation across modalities. We further specified evaluation metrics and developed a cloud-based algorithm evaluation pipeline. Using this setup, 280 competitors submitted over 2600 proposed solutions within a 3 month period, showcasing substantial innovation especially in the modality alignment task. Here, we present the results, describe trends of well performing approaches, and discuss challenges associated with running the competition.

bioinformatics↗

bioRxiv2022

Motifizer: a tool for parsing high-throughput sequencing datasets and quantitative comparative analyses of transcription factor-binding sites

BackgroundComparative analysis of Chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq), combined with transcriptomics data (RNA-seq), can provide critical insights into gene regulatory networks controlled by transcription factors in a given biological context. While multiple programs exist, which need to be individually installed and executed to generate such information, a user-friendly tool with low system requirements which combines the various computational processes into one package, using a docker container, is lacking. ResultsIn this study, we present a user-interactive, infrastructure-independent computational pipeline, called Motifizer, which uses open source tools for processing ChIP-Seq and RNA-seq datasets. Motifizer performs extensive analysis of raw input data, performing peak calling, de-novo motif analysis and differential gene expression analysis on ChIP and RNA-seq datasets. Additionally, Motifizer can be used for analysis and quantitative comparison of transcription factor binding sites in user defined genomic regions. Motifizer also allows easy addition and/or changes of parameters, thereby adding to the versatility of the tool. ConclusionThe Motifizer tool is an easy to use tool which uses a docker container system to install and execute ChIP-seq and RNA-seq data parsing. The Analysis module of Motifizer can be employed to identify putative targets involved in gene regulatory networks. Motifizer can be accessed by a large user base and does not require programming skill by the user. Motifizer can be locally installed from the repository (https://github.com/abhikbhattacharjee/Motifizer)

bioinformatics↗

bioRxiv2022

Extracellular vesicle fusion visualized by cryo-EM

Extracellular vesicles (EVs) transfer bioactive molecules between cells in a process reminiscent of enveloped viruses. EV cargo delivery is thought to occur by protein-mediated and pH-dependent membrane fusion of the EV and the cellular membrane. However, there is a lack of methods to identify the fusion proteins and resolve their mechanism. We developed and benchmarked an in vitro biophysical assay to investigate EV membrane fusion. The assay was standardized by directly comparing EV- and viral-fusion with liposomes. We show that EVs and retroviruses fuse with liposomes mimicking the membrane composition of the late endosome in a pH and protein-dependent manner. Moreover, we directly visualize the stages of membrane fusion using cryo-electron tomography. We find that, unlike most retroviruses, EVs remain fusogenic after acidification and re-neutralization. These results provide novel insights into the EV cargo delivery mechanism and an experimental approach to identify the EV fusion machinery.

biophysics↗

bioRxiv2022

Prioritized single-cell proteomics reveals molecular and functional polarization across primary macrophages

Major aims of single-cell proteomics include increasing the consistency, sensitivity, and depth of protein quantification, especially for proteins and modifications of biological interest. To simultaneously advance all these aims, we developed prioritized Single Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth. These strategies increased the sensitivity, data completeness, and proteome coverage over 2-fold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport. This protein covariation within a treatment condition was similar across the treatment conditions and coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at: scp.slavovlab.net/pSCoPE O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/484655v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@c44f04org.highwire.dtl.DTLVardef@1fb3e8org.highwire.dtl.DTLVardef@15c456eorg.highwire.dtl.DTLVardef@d271e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

In vitro direct regeneration and Agrobacterium tumefaciens mediated in planta transformation of Ocimum sanctum L.

Ocimum sanctum is a multipurpose herb with highly significant medicinal properties. An in vitro direct regeneration protocol for propagation of a valuable medicinal plant Ocimum sanctum, using petiole explants has been successfully developed. The protocol employed regeneration of shoots directly, without any intervening callus using Murashige and Skoog (MS) medium fortified with 3 mg L-1 BAP + 1 mg L-1 NAA. The maximum regeneration frequency of 98% with 9.6 shoots per explants was achieved. Agrobacterium tumefaciens mediated genetic transformation (ATMT) protocol (transient and stable) was established using LBA4404 strain harboring pBI121 with uid-A reporter gene and neomycin phosphotransferase (npt-II) as selection marker. The putative transformants were screened on MS with 50 mg L-1 kanamycin and subsequently rooted on the half-strength MS medium. The confirmation was done via polymerase chain reaction (PCR) using npt-II and gus-A gene-specific primers. The maximum stable transformation frequency 70% {+/-} 0.35. Thus, it is apparent that the established in vitro direct regeneration and ATMT method was suitable for integrating novel genes and modulating the metabolic flux for obtaining desired agronomic trait in planta.

plant biology↗

bioRxiv2022

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.

cancer biology↗

bioRxiv2022

GWAS and functional studies implicate a role for altered DNA repair in the evolution of drug resistance in Mycobacterium tuberculosis

The emergence of drug resistance in Mycobacterium tuberculosis (Mtb) is alarming and demands in-depth knowledge for timely diagnosis. We performed genome-wide association analysis (GWAS) using 2237 clinical strains of Mtb to identify novel genetic factors that evoke drug resistance. In addition to the known direct targets, for the first time, we identified a strong association between the mutations in the DNA repair genes and the multidrug-resistant phenotype. To evaluate the impact of variants identified in the clinical samples in the evolution of drug resistance, we utilized knockouts and complemented strains in Mycobacterium smegmatis (Msm) and Mtb. Results show that variant mutations abrogated the function of MutY and UvrB. MutY variant showed enhanced survival compared with wild-type (Rv) when the Mtb strains were subjected to multiple rounds of ex vivo antibiotic stress. Notably, in an in vivo Guinea pig infection model, the MutY variant outcompeted the wild-type strain. Collectively, we show that novel variant mutations in the DNA repair genes abrogate their function and contribute to better survival under antibiotic/host stress conditions.

microbiology↗

bioRxiv2021

Matchtigs: minimum plain text representation of kmer sets

We propose a polynomial algorithm computing a minimum plain-text representation of kmer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 60% over unitigs and 27% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 91% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26x over unitigs and 2.10x over previous work. Availabilitymatchtigs: https://github.com/algbio/matchtigs SSHash-Lite: https://github.com/jermp/sshash-lite

bioinformatics↗