Publications by authors named "Brinda K"

Unlabelled: Timely diagnostic tools are needed to improve antibiotic treatment. Pairing metagenomic sequencing with genomic neighbor typing algorithms may support rapid clinically actionable results. We created resistance-associated sequence elements (RASE) databases for and .

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Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections has made it effectively impossible to search these data using tools such as BLAST and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures.

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State-level reopenings in late spring 2020 facilitated the resurgence of severe acute respiratory syndrome coronavirus 2 transmission. Here, we analyze age-structured case, hospitalization, and death time series from three states-Rhode Island, Massachusetts, and Pennsylvania-that had successful reopenings in May 2020 without summer waves of infection. Using 11 daily data streams, we show that from spring to summer, the epidemic shifted from an older to a younger age profile and that elderly individuals were less able to reduce contacts during the lockdown period when compared to younger individuals.

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Background: Our interconnected world and the ability of bacteria to quickly swap antibiotic resistance genes (ARGs) make it particularly important to establish the epidemiological links of multidrug resistance (MDR) transfer between wastewater treatment plant (WWTP)- and human/animal-associated bacteria, under the One Health framework. However, evidence of ARGs exchange and potential factors that contribute to this transfer remain limited.

Results: Here, by combining culture-based population genomics and genetic comparisons with publicly available datasets, we reconstructed the complete genomes of 82 multidrug-resistant isolates from WWTPs and found that most WWTP-associated isolates were genetically distinct from their closest human/animal-associated relatives currently available in the public database.

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In the United States, state-level re-openings in spring 2020 presented an opportunity for the resurgence of SARS-CoV-2 transmission. One important question during this time was whether human contact and mixing patterns could increase gradually without increasing viral transmission, the rationale being that new mixing patterns would likely be associated with improved distancing, masking, and hygiene practices. A second key question to follow during this time was whether clinical characteristics of the epidemic would improve after the initial surge of cases.

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Background: When three SARS-CoV-2 vaccines came to market in Europe and North America in the winter of 2020-2021, distribution networks were in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation was critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs likely require that distribution is prioritized to the elderly, health care workers, teachers, essential workers, and individuals with comorbidities putting them at risk of severe clinical progression.

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de Bruijn graphs play an essential role in bioinformatics, yet they lack a universal scalable representation. Here, we introduce simplitigs as a compact, efficient, and scalable representation, and ProphAsm, a fast algorithm for their computation. For the example of assemblies of model organisms and two bacterial pan-genomes, we compare simplitigs to unitigs, the best existing representation, and demonstrate that simplitigs provide a substantial improvement in the cumulative sequence length and their number.

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It is well established that plasmids play an important role in the dissemination of antimicrobial resistance (AMR) genes; however, little is known about the role of the underlying interactions between different plasmid categories and other mobile genetic elements (MGEs) in shaping the promiscuous spread of AMR genes. Here, we developed a tool designed for plasmid classification, AMR gene annotation, and plasmid visualization and found that most plasmid-borne AMR genes, including those localized on class 1 integrons, are enriched in conjugative plasmids. Notably, we report the discovery and characterization of a massive insertion sequence (IS)-associated AMR gene transfer network (245 combinations covering 59 AMR gene subtypes and 53 ISs) linking conjugative plasmids and phylogenetically distant pathogens, suggesting a general evolutionary mechanism for the horizontal transfer of AMR genes mediated by the interaction between conjugative plasmids and ISs.

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As three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression.

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The rising rates of antibiotic resistance increasingly compromise empirical treatment. Knowing the antibiotic susceptibility of a pathogen's close genetic relative(s) may improve empirical antibiotic selection. Using genomic and phenotypic data for isolates from three separate clinically derived databases, we evaluated multiple genomic methods and statistical models for predicting antibiotic susceptibility, focusing on potentially rapidly available information, such as lineage or genetic distance from archived isolates.

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Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata.

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Glucose oxidase mimicking nickel-based porous structures with organic anchors are developed as cheap and reliable electrochemical sensors for the quantitative detection of glucose. A series of sterically and electronically modulated, air- and moisture-stable half-sandwich nickel(II) NHC complexes were prepared and characterized. Under the optimized electrocatalytic conditions, the nickel complex immobilized glassy carbon electrodes (GCEs) displayed high sensitivity (0.

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Here, we report the synthesis and magnetic properties of a new triangular lattice antiferromagnet BaCoTaO. The effective spin of Co is found to be J  =  1/2 at low temperatures due to the combined effect of crystal field and spin-orbit coupling. BaCoTaO undergoes two successive magnetic phase transitions at [Formula: see text] K and [Formula: see text] K in zero applied field, which is typical for triangular antiferromagnets with the easy-axis magnetic anisotropy.

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Motivation: Read simulators combined with alignment evaluation tools provide the most straightforward way to evaluate and compare mappers. Simulation of reads is accompanied by information about their positions in the source genome. This information is then used to evaluate alignments produced by the mapper.

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Motivation: Metagenomics is a powerful approach to study genetic content of environmental samples, which has been strongly promoted by next-generation sequencing technologies. To cope with massive data involved in modern metagenomic projects, recent tools rely on the analysis of k-mers shared between the read to be classified and sampled reference genomes.

Results: Within this general framework, we show that spaced seeds provide a significant improvement of classification accuracy, as opposed to traditional contiguous k-mers.

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Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure.

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Recently we showed that the three-dimensional structure of proteins can be investigated from a network perspective, where the amino acid residues represent the nodes in the network and the noncovalent interactions between them are considered for the edge formation. In this study, the dynamical behavior of such networks is examined by considering the example of T4 lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein at 300 K and at higher temperatures (400 K and 500 K), respectively.

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The structure networks of DNA-binding proteins have been constructed and analyzed. The detailed analysis of the networks indicates a strong relation between the positions of the residues interacting with DNA and those that form extensive interactions within the protein structure (called hubs). This study shows that the functional residues in these proteins are held in place by efficient scaffolding of the structure using side-chain interactions, thus highlighting the role of these side-chain hubs with respect to the functional residues in the protein structure.

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Background: Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues.

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The unique three-dimensional structure of both monomeric and oligomeric proteins is encoded in their sequence. The biological functions of proteins are dependent on their tertiary and quaternary structures, and hence it is important to understand the determinants of quaternary association in proteins. Although a large number of investigations have been carried out in this direction, the underlying principles of protein oligomerization are yet to be completely understood.

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This study views each protein structure as a network of noncovalent connections between amino acid side chains. Each amino acid in a protein structure is a node, and the strength of the noncovalent interactions between two amino acids is evaluated for edge determination. The protein structure graphs (PSGs) for 232 proteins have been constructed as a function of the cutoff of the amino acid interaction strength at a few carefully chosen values.

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We present a simple method for the analysis of large networks based on their graph spectral properties. One of the advantages of this method is that it uses a single numerical computation to identify subclusters in a connected graph, which can significantly simplify the complexity involved in analyzing large graphs. This is illustrated using a network of protein chains constructed on the basis of their structural similarities.

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It is well known that the sequence of amino acids in proteins code for its tertiary structure. It is also known that there exists a relationship between sequence and the quaternary structure of proteins. The question addressed here is whether the nature of quaternary association can be predicted from the sequence, similar to the three-dimensional structure prediction from the sequence.

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