Array2BIO: from microarray expression data to functional annotation of co-regulated genes

BACKGROUND: There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. RESULTS: Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1) comparative analysis of signal versus control and (2) clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. CONCLUSION: We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available a

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Edited by:

The cross-talk between spirochetal lipoprotein

Safety and efficacy of C. muridarum vaccines adjuvanted with CpG-1826 and four concentrations of Montanide-ISA-720-VG.

It is recommended that the adjuvant Montanide ISA 720 VG be used at a concentration of 70% v/v. At this concentration, Montanide causes at the site of immunization a local granuloma that can last for several weeks. To determine the safety and protective efficacy of a Chlamydia muridarum MOMP vaccine, formulated with CpG-1826 and four different concentrations of Montanide (70%, 50%, 30% and 10%), BALB/c (H-2d) female mice were immunized twice intramuscularly. Local reactogenicity was significant for vaccines formulated with 70% or 50% Montanide but not for those inoculated with 30% or 10% Montanide. Robust humoral and cell mediated memory immune responses were elicited by the 70%, 50% and 30% Montanide formulations. Mice were challenged intranasally with 104 C. muridarum inclusion forming units (IFU). Based on changes in body weight, lungss weight and number of IFU recovered, mice vaccinated with the 70%, 50% and 30% Montanide formulations were significantly protected, but not mice receiving 10% Montanide. To conclude, we recommend the 30% Montanide concentration to be tested in humans and animal models to determine its safety and efficacy, in comparison to the 70% Montanide concentration currently used. The 30% Montanide formulation could significantly facilitate licensing of this adjuvant for human use

Metabolic Profiling of Volatile Organic Compounds (VOCs) Emitted by the Pathogens Francisella tularensis and Bacillus anthracis in Liquid Culture

Abstract We conducted comprehensive (untargeted) metabolic profiling of volatile organic compounds (VOCs) emitted in culture by bacterial taxa Francisella tularensis (F. tularensis) subspecies novicida and Bacillus anthracis (B. anthracis) Sterne, surrogates for potential bacterial bioterrorism agents, as well as selective measurements of VOCs from their fully virulent counterparts, F. tularensis subspecies tularensis strain SCHU S4 and B. anthracis Ames. F. tularensis and B. anthracis were grown in liquid broth for time periods that covered logarithmic growth, stationary, and decline phases. VOCs emitted over the course of the growth phases were collected from the headspace above the cultures using solid phase microextraction (SPME) and were analyzed using gas chromatography-mass spectrometry (GC-MS). We developed criteria for distinguishing VOCs originating from bacteria versus background VOCs (originating from growth media only controls or sampling devices). Analyses of collected VOCs revealed methyl ketones, alcohols, esters, carboxylic acids, and nitrogen- and sulfur-containing compounds that were present in the bacterial cultures and absent (or present at only low abundance) in control samples indicating that these compounds originated from the bacteria. Distinct VOC profiles where observed for F. tularensis when compared with B. anthracis while the observed profiles of each of the two F. tularensis and B. anthracis strains exhibited some similarities. Furthermore, the relative abundance of VOCs was influenced by bacterial growth phase. These data illustrate the potential for VOC profiles to distinguish pathogens at the genus and species-level and to discriminate bacterial growth phases. The determination of VOC profiles lays the groundwork for non-invasive probes of bacterial metabolism and offers prospects for detection of microbe-specific VOC biomarkers from two potential biowarfare agents

Francisella tularensis Type A Strains Cause the Rapid Encystment of Acanthamoeba castellanii and Survive in Amoebal Cysts for Three Weeks Postinfection ▿

Francisella tularensis, the causative agent of the zoonotic disease tularemia, has recently gained increased attention due to the emergence of tularemia in geographical areas where the disease has been previously unknown and to the organism's potential as a bioterrorism agent. Although F. tularensis has an extremely broad host range, the bacterial reservoir in nature has not been conclusively identified. In this study, the ability of virulent F. tularensis strains to survive and replicate in the amoeba Acanthamoeba castellanii was explored. We observe that A. castellanii trophozoites rapidly encyst in response to F. tularensis infection and that this rapid encystment phenotype is caused by factor(s) secreted by amoebae and/or F. tularensis into the coculture medium. Further, our results indicate that in contrast to the live vaccine strain LVS, virulent strains of F. tularensis can survive in A. castellanii cysts for at least 3 weeks postinfection and that the induction of rapid amoeba encystment is essential for survival. In addition, our data indicate that pathogenic F. tularensis strains block lysosomal fusion in A. castellanii. Taken together, these data suggest that interactions between F. tularensis strains and amoebae may play a role in the environmental persistence of F. tularensis