Zinc binding and chelating compounds as inhibitors of bacterial metalloproteases and human matrix metalloproteases

Bacterial multi-drug resistance is a major health problem worldwide. Inhibition of bacterial virulence is suggested to be a promising strategy in the development of new antibacterial drugs. The present work has focused on identifying new inhibitors of the bacterial virulence factors thermolysin (TLN), pseudolysin (PLN, LasB) and aureolysin (ALN), which are all zinc metalloproteases (MPs) using enzyme kinetics studies and molecular modelling. A chemical group chelating the catalytic zinc ion of MPs, referred to as the zinc-binding group (ZBG) (e.g., phosphinate (PO2), carboxylate (COO-), thiolate (S-) and hydroxamic acid HONH-CO, sulfhydryl, etc.) is important for essential inhibition. The strategy in the present work was to use different compounds with a putative ZBG, including compounds with nitrogen as the zinc donor atom. The structure of the active site cleft of the virulence factors is very similar to that of the matrix metalloproteases (MMPs) and other human zinc MPs. Bacterial virulence inhibitors as drugs against bacterial infections should have limited effects on human endogenous zinc MPs. Therefore, we also tested their inhibition of human MMP-9 and MMP-14. Several compounds were found to inhibit the activity of the virulence factors, but most of the compounds also inhibited the human enzymes. However, the studies showed that the bisphosphonate-containing compound RC2 bound stronger to the bacterial virulence factors than to the human enzymes, while the catechol-containing compound BF471 was found to inhibit ALN. To our knowledge, this is the first reported small molecule inhibiting ALN. These compounds may be used as scaffolds to design new and potentially stronger inhibitors of bacterial virulence factors with therapeutic potential

Compression Algorithm for Colored de Bruijn Graphs

A colored de Bruijn graph (also called a set of k-mer sets), is a set of k-mers with every k-mer assigned a set of colors. Colored de Bruijn graphs are used in a variety of applications, including variant calling, genome assembly, and database search. However, their size has posed a scalability challenge to algorithm developers and users. There have been numerous indexing data structures proposed that allow to store the graph compactly while supporting fast query operations. However, disk compression algorithms, which do not need to support queries on the compressed data and can thus be more space-efficient, have received little attention. The dearth of specialized compression tools has been a detriment to tool developers, tool users, and reproducibility efforts. In this paper, we develop a new tool that compresses colored de Bruijn graphs to disk, building on previous ideas for compression of k-mer sets and indexing colored de Bruijn graphs. We test our tool, called ESS-color, on various datasets, including both sequencing data and whole genomes. ESS-color achieves better compression than all evaluated tools and all datasets, with no other tool able to consistently achieve less than 44% space overhead

Disk Compression of k-mer Sets

K-mer based methods have become prevalent in many areas of bioinformatics. In applications such as database search, they often work with large multi-terabyte-sized datasets. Storing such large datasets is a detriment to tool developers, tool users, and reproducibility efforts. General purpose compressors like gzip, or those designed for read data, are sub-optimal because they do not take into account the specific redundancy pattern in k-mer sets. In our earlier work (Rahman and Medvedev, RECOMB 2020), we presented an algorithm UST-Compress that uses a spectrum-preserving string set representation to compress a set of k-mers to disk. In this paper, we present two improved methods for disk compression of k-mer sets, called ESS-Compress and ESS-Tip-Compress. They use a more relaxed notion of string set representation to further remove redundancy from the representation of UST-Compress. We explore their behavior both theoretically and on real data. We show that they improve the compression sizes achieved by UST-Compress by up to 27 percent, across a breadth of datasets. We also derive lower bounds on how well this type of compression strategy can hope to do

The K-mer File Format: a standardized and compact disk representation of sets of k-mers

International audienceBioinformatics applications increasingly rely on ad hoc disk storage of k-mer sets, e.g. for de Bruijn graphs or alignment indexes. Here, we introduce the K-mer File Format as a general lossless framework for storing and manipulating k-mer sets, realizing space savings of 3–5× compared to other formats, and bringing interoperability across tools. Availability: Format specification, C++/Rust API, tools: https://github.com/Kmer-File-Format/

Assessment of mortality from COVID-19 in a multicultural multi-ethnic patient population.

BackgroundStudies indicate that ethnicity and socioeconomic disparity are significant facilitators for COVID-19 mortality. The United Arab Emirates, distinctly has a population of almost 12% citizens and the rest, immigrants, are mainly unskilled labourers. The disparate socio-economic structure, crowded housing conditions, and multi-ethnic population offer a unique set of challenges in COVID-19 management.MethodsPatient characteristics, comorbidities, and clinical outcomes data from the electronic patient medical records were retrospectively extracted from the hospital information system of the two designated public COVID-19 referral hospitals. Chi-square test, logistic regression, and odds ratio were used to analyse the variables.ResultsFrom, the total of 3072 patients, less than one-fifth were females; the Asian population (71.2%);followed by Middle Eastern Arabs (23.3%) were the most infected by the virus. Diabetes Mellitus (26.8%), hypertension (25.7%) and heart disease (9.6%) were the most prevalent comorbidities observed among COVID-19 patients. Kidney disease as comorbidity significantly diminished the survival rates (Crude OR 9.6, 95% CI (5.6-16.6), p ConclusionOur study indicates that older ages above 51 years and kidney disease increased mortality significantly in COVID-19 patients. Ethnicity was not significantly associated with mortality in the UAE population. Our findings are important in the management of the COVID-19 disease in the region with similar economic, social, cultural, and ethnic backgrounds