Biology subjects

Sekar, S.

Publications and source records attributed to Sekar, S..

8 recordsLinked to original sources

bioRxiv2026

A widespread SCCmec-located gene cluster protects methicillin-resistant Staphylococcus aureus against toxic polysulfides

The genus Staphylococcus contains important human commensals and pathogens, including methicillin-resistant Staphylococcus aureus (MRSA), which is a frequent colonizer of humans and a leading cause of healthcare-associated and life-threatening infections. While its virulence and pathogenicity have been extensively studied, factors driving the colonization and distribution of MRSA as a pathobiont are less understood. Here, we report on a cst sulfide detoxification gene cluster located on SCCmec, the antibiotic resistance-mediating genetic element of MRSA. Bioinformatic analyses revealed a heterogeneous distribution of cst clusters in staphylococcal genomes and that many clinically relevant SCCmec types introduce an additional cst cluster (cst2) to MRSA. While the canonical cst cluster (cst1) consists of the five genes tauE, cstR, cstA, cstB, and sqr, most staphylococcal cst clusters, including the SCCmec-located cst2, lack the sqr gene, which encodes for a sulfide:quinone reductase responsible for the initial step of sulfide detoxification. Growth experiments with a diverse set of representative Staphylococcus strains, cst-deletion mutants, and complementation with cst-containing plasmids demonstrated that the cst cluster enables sqr-independent polysulfide-detoxification. Furthermore, the additional cst2 cluster confers high polysulfide tolerance to MRSA, providing the pathogen with a unique advantage in polysulfide-rich environments. Using serial passaging co-cultivation experiments with methicillin-sensitive S. aureus (MSSA) strains, we demonstrated that in the presence of polysulfides cst2-containing MRSA can invade an established MSSA population and outperform the occupying resident in direct competition. Overall, our findings indicate that polysulfides are critical stress factors for staphylococci, potentially contributing to the spread of cst2-containing SCCmec and MRSA. ImportanceMethicillin-resistant Staphylococcus aureus (MRSA) is one of the most prevalent human pathogens responsible for millions of life-threatening infections worldwide. It acquires antibiotic resistance through the genetic element SCCmec, which contains the characteristic mecA gene that renders the organism resistant to most classes of {beta}-lactam antibiotics. Besides mecA and accessory gene complexes necessary for the transfer of SCCmec and phenotype manifestation, the genetic element also contains prominent gene clusters with unknown functions. Here, we report on a (poly-)sulfide-detoxification gene cluster (cst2) present on SCCmec that provides MRSA with a unique advantage in environments containing polysulfides - highly reactive intermediates of sulfide oxidation naturally occurring as microbial stressors on mucosal surfaces inside the human body. We demonstrate that in the presence of polysulfides, cst2 enables MRSA to outperform non-MRSA in direct competition, thus supporting the invasion and proliferation of this pathogen independent of its antibiotic resistance.

microbiology↗

bioRxiv2024

EEG data quality in large scale field studies in India and Tanzania

There is a growing imperative to understand the neurophysiological impact of our rapidly changing and diverse technological, social, chemical, and physical environments. To untangle the multidimensional and interacting effects requires data at scale across diverse populations, taking measurement out of a controlled lab environment and into the field. Electroencephalography (EEG), which has correlates with various environmental factors as well as cognitive and mental health outcomes, has the advantage of both portability and cost-effectiveness for this purpose. However, with numerous field researchers spread across diverse locations, data quality issues and researcher idle time due to insufficient participants can quickly become unmanageable and expensive problems. In programs we have established in India and Tanzania, we demonstrate that with appropriate training, structured teams, and daily automated analysis and feedback on data quality, non-specialists can reliably collect EEG data alongside various survey and assessments with consistently high throughput and quality. Over a 30-week period, research teams were able to maintain an average of 25.6 subjects per week, collecting data from a diverse sample of 7,933 participants ranging from Hadzabe hunter-gatherers to office workers. Furthermore, data quality, computed on the first 2,400 records using two common methods, PREP and FASTER, was comparable to benchmark datasets from controlled lab conditions. Altogether this resulted in a cost per subject of under $50, a fraction of the cost typical of such data collection, opening up the possibility for large-scale programs particularly in low- and middle-income countries. Significance StatementWith wide human diversity, a rapidly changing environment and growing rates of neurological and mental health disorders, there is an imperative for large scale neuroimaging studies across diverse populations that can deliver high quality data and be affordably sustained. Here we demonstrate, across two large-scale field data acquisition programs operating in India and Tanzania, that with appropriate systems it is possible to generate high throughput EEG data of quality comparable to controlled lab settings. With effective costs of under $50 per subject, this opens new possibilities for low- and middle-income countries to implement large-scale programs, and to do so at scales that previously could not be considered.

neuroscience↗

bioRxiv2022

Impact of late larval nutritional stress on adult metabolic, gut and locomotor phenotypes in Drosophila melanogaster

Dietary quantity and quality are key determinants for insect development from egg to adult. When nutritional deficiency is sub-optimal, development is completed, albeit resulting in an adult insect that is smaller than normal in size. If now fed a normal diet, would the smaller adults be similar to normally developed flies? To begin to answer this question, we characterised a few physiological and musculoskeletal readouts. Larvae were subject to acute starvation in late stages of development, and the resulting adults (Early Life Starved; ELS) maintained on a normal diet, were tested for biochemistry, gut physiology and locomotor activity. In females, no significant difference was observed in biochemical readouts for the whole-body or hemolymph, between control and ELS flies. In males, whole-body glucose and hemolymph trehalose were significantly reduced in ELS flies. Interestingly, ELS flies of both sexes respond with a disproportionally higher accumulation of triacylglycerides (TAGs) when on a high-fat diet. Age-related changes in the adult gut were compared between control and ELS flies: these revealed an increased proportion of ELS flies with loss of gut barrier integrity, deviant number of intestinal stem cells and no difference in enteroendocrine cells. The rate of antimicrobial peptide gene expression to an enteric infection challenge was also slower in ELS flies. For musculoskeletal readouts, climbing and flight behaviour were measured. In population assays, both male and female ELS flies showed climbing deficits. In a fine-scale climbing assay on individual flies, female but not male ELS flies showed higher climbing speed, while males but not females, showed lower geotactic index. This collection of phenotypic assessments show that firstly, larval undernutrition, even when not lethal, continues to impact adult functioning. Secondly, for some phenotypes, a normal diet in adults exposed to early life malnutrition is insufficient to restore optimal functioning. Thirdly, larval dietary loss affects adult insects in a sex-dependent manner. This study lays the framework to uncover the molecular, cellular and hormonal mechanisms that are altered by early life malnutrition. Furthermore, these readouts may be used to develop Drosophila as a high-throughput model for interrogating the efficacy of diet therapies to address malnutrition.

developmental biology↗

bioRxiv2021

All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons

Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing cells genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell from exhaustive comparison of cells genomes to each other without data for bulk(s). Based on all pair-wise comparisons, every variant call (point mutation, indel, and structural variant) is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing. All2 is freely available at https://github.com/abyzovlab/All2.

bioinformatics↗

bioRxiv2020

Pubertal androgens reduce the effects of social stress on anxiety-related behaviors in California mice

Anxiety disorders are more common in women than men, and this difference arises during puberty. Increased secretion of gonadal hormones during puberty influences brain structure and function, but the extent to which hormones modulate anxiety-related brain circuits is unclear. The slow developing California mouse (Peromyscus californicus) is an ideal species for studying the effects of hormones on brain function during adolescence. In adults social defeat stress reduces social approach and increases vigilance in females but not males. Here we show this sex difference is absent in juvenile mice, and that prepubertal castration sensitizes adult males to social defeat. Since adult castration has no effect on stress sensitivity, our data show that gonadal hormones act during puberty to program behavioral responses to stress later in life. In adults, calcium imaging in the medioventral bed nucleus of the stria terminalis shows that threatening social contexts increase calcium transients. Furthermore, prepubertal castration generalizes these responses to less threatening social contexts. Prepubertal treatment with the non-aromatizable androgen dihydrotestosterone acts in males and females to reduce sensitivity to social defeat in adults. Together, these data indicate activation of androgen receptors during puberty are critical for programing behavioral responses to stress in adulthood, highlighting a possible mechanism contributing to sex differences in anxiety. Significance StatementPuberty is a key period when sex differences in anxiety emerges. Gonadal hormone release increases during this time but it is largely unknown how they impact brain circuits and behavior. We show that androgens play a key role in programming behavioral responses to social defeat stress. The bed nucleus of the stria terminalis responds to social threats and these responses are more generalized in males without gonadal hormone exposure during puberty. Our findings highlight the importance of pubertal androgens in determining adult behavioral responses to social stress.

developmental biology↗

bioRxiv2020

Comprehensive identification of somatic nucleotide variants in human brain tissue

Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. Here, the Brain Somatic Mosaicism Network conducted a coordinated, multi-institutional study to: (i) examine the ability of existing methods to detect simulated somatic single nucleotide variants (SNVs) in DNA mixing experiments; (ii) generate multiple replicates of whole genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual; (iii) devise strategies to discover somatic SNVs; and (iv) apply various approaches to validate somatic SNVs. These efforts led to the identification of 43 bona fide somatic SNVs that ranged in variant allele fractions from ~0.005 to ~0.28. Guided by these results, we devised best practices for calling mosaic SNVs from 250X whole genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrated that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Thus, this study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

genomics↗

bioRxiv2019

ACValidator: a novel assembly-based approach for in silico validation of circular RNAs

Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons back-splice to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true positive circRNAs. To this end, we developed ACValidator (Assembly based CircRNA Validator) for in silico validation of circRNAs. ACValidator extracts reads from a user-defined window on either side of the circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the backspliced junction. When evaluated on simulated datasets, ACValidator achieved over 80% sensitivity and specificity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher validation percentages for samples treated with ribonuclease R compared to non-treated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for experimental validations. All workflow scripts are freely accessible on our github page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator. Author summaryCircular RNAs (circRNAs) are a recent addition to the class of non-coding RNAs and are produced when exons back-splice and form closed circular loops. Although several computational algorithms have been developed to detect circRNAs from RNA sequencing (RNAseq) data, they produce divergent results. We hence developed the software Assembly based Circular RNA Validator (ACValidator) as an orthogonal strategy to separately validate predicted circRNAs in silico. ACValidator takes as input a sequence alignment mapping (SAM) file and the circRNA coordinate(s) to be validated. Reads surrounding the circRNA junction are extracted from the SAM file and assembled to generate contigs. These contigs are then aligned against the circRNA sequence to identify contigs that span the back-spliced junction. We evaluated our workflow on simulated as well as experimental datasets to demonstrate the utility of our approach. ACValidator is implemented in python and is highly computationally efficient, with a run time of less than 2 minutes for an 8 GB SAM file. This workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for experimental validations.

bioinformatics↗

bioRxiv2018

Circular RNA expression and regulatory network prediction in posterior cingulate astrocytes in elderly subjects

BackgroundCircular RNAs (circRNAs) are a novel class of endogenous, non-coding RNAs that form covalently closed continuous loops and are both highly conserved and abundant in the mammalian brain. A role for circRNAs in sponging microRNAs (miRNAs) has been proposed, but the circRNA-miRNA-mRNA interaction networks in human brain cells have not been defined. Therefore, we identified circRNAs in RNA sequencing data previously generated from astrocytes microdissected from the posterior cingulate (PC) of Alzheimers disease (AD) patients (N=10) and healthy elderly controls (N=10) using four circRNA prediction algorithms - CIRI, CIRCexplorer, find_circ and KNIFE.\n\nResultsOverall, utilizing these four tools, we identified a union of 4,438 unique circRNAs across all samples, of which 70.3% were derived from exonic regions. Notably, the widely reported CDR1as circRNA was detected in all samples across both groups by find_circ. Given the putative miRNA regulatory function of circRNAs, we identified potential miRNA targets of circRNAs, and further, delineated circRNA-miRNA-mRNA networks using in silico methods. Pathway analysis of the genes regulated by these miRNAs identified significantly enriched immune response pathways, which is consistent with the known function of astrocytes as immune sensors in the brain.\n\nConclusionsIn this study, we performed circRNA detection on cell-specific transcriptomic data and identified potential circRNA-miRNA-mRNA regulatory networks in PC astrocytes. Given the known function of astrocytes in cerebral innate immunity and our identification of significantly enriched immune response pathways, the circRNAs we identified may be associated with such key functions. While we did not detect recurrent differentially expressed circRNAs in the context of healthy controls or Alzheimers, we report for the first time circRNAs and their potential regulatory impact in a cell-specific and region-specific manner in aged subjects. These predicted regulatory network and pathway analyses may help provide new insights into transcriptional regulation in the brain.

neuroscience↗