University of Massachusetts Medical School

About: University of Massachusetts Medical School is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Population & Health care. The organization has 16161 authors who have published 31822 publications receiving 1909739 citations. The organization is also known as: UMass Medical School.

High-resolution Phenotypic Profiling Defines Genes Essential for Mycobacterial Growth and Cholesterol Catabolism

Abstract: The pathways that comprise cellular metabolism are highly interconnected, and alterations in individual enzymes can have far-reaching effects. As a result, global profiling methods that measure gene expression are of limited value in predicting how the loss of an individual function will affect the cell. In this work, we employed a new method of global phenotypic profiling to directly define the genes required for the growth of Mycobacterium tuberculosis. A combination of high-density mutagenesis and deep-sequencing was used to characterize the composition of complex mutant libraries exposed to different conditions. This allowed the unambiguous identification of the genes that are essential for Mtb to grow in vitro, and proved to be a significant improvement over previous approaches. To further explore functions that are required for persistence in the host, we defined the pathways necessary for the utilization of cholesterol, a critical carbon source during infection. Few of the genes we identified had previously been implicated in this adaptation by transcriptional profiling, and only a fraction were encoded in the chromosomal region known to encode sterol catabolic functions. These genes comprise an unexpectedly large percentage of those previously shown to be required for bacterial growth in mouse tissue. Thus, this single nutritional change accounts for a significant fraction of the adaption to the host. This work provides the most comprehensive genetic characterization of a sterol catabolic pathway to date, suggests putative roles for uncharacterized virulence genes, and precisely maps genes encoding potential drug targets.

ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data

Abstract: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome. We have developed ChIPpeakAnno as a Bioconductor package within the statistical programming environment R to facilitate batch annotation of enriched peaks identified from ChIP-seq, ChIP-chip, cap analysis of gene expression (CAGE) or any experiments resulting in a large number of enriched genomic regions. The binding sites annotated with ChIPpeakAnno can be viewed easily as a table, a pie chart or plotted in histogram form, i.e., the distribution of distances to the nearest genes for each set of peaks. In addition, we have implemented functionalities for determining the significance of overlap between replicates or binding sites among transcription factors within a complex, and for drawing Venn diagrams to visualize the extent of the overlap between replicates. Furthermore, the package includes functionalities to retrieve sequences flanking putative binding sites for PCR amplification, cloning, or motif discovery, and to identify Gene Ontology (GO) terms associated with adjacent genes. ChIPpeakAnno enables batch annotation of the binding sites identified from ChIP-seq, ChIP-chip, CAGE or any technology that results in a large number of enriched genomic regions within the statistical programming environment R. Allowing users to pass their own annotation data such as a different Chromatin immunoprecipitation (ChIP) preparation and a dataset from literature, or existing annotation packages, such as GenomicFeatures and BSgenom e, provides flexibility. Tight integration to the biomaRt package enables up-to-date annotation retrieval from the BioMart database.

Attitudes Toward a Potential SARS-CoV-2 Vaccine: A Survey of U.S. Adults.

Abstract: Background Coronavirus disease 2019 (COVID-19) has rapidly instigated a global pandemic. Vaccine development is proceeding at an unprecedented pace. Once available, it will be important to maximize vaccine uptake and coverage. Objective To assess intent to be vaccinated against COVID-19 among a representative sample of adults in the United States and identify predictors of and reasons for vaccine hesitancy. Design Cross-sectional survey, fielded from 16 through 20 April 2020. Setting Representative sample of adults residing in the United States. Participants Approximately 1000 adults drawn from the AmeriSpeak probability-based research panel, covering approximately 97% of the U.S. household population. Measurements Intent to be vaccinated against COVID-19 was measured with the question, "When a vaccine for the coronavirus becomes available, will you get vaccinated?" Response options were "yes," "no," and "not sure." Participants who responded "no" or "not sure" were asked to provide a reason. Results A total of 991 AmeriSpeak panel members responded. Overall, 57.6% of participants (n = 571) intended to be vaccinated, 31.6% (n = 313) were not sure, and 10.8% (n = 107) did not intend to be vaccinated. Factors independently associated with vaccine hesitancy (a response of "no" or "not sure") included younger age, Black race, lower educational attainment, and not having received the influenza vaccine in the prior year. Reasons for vaccine hesitancy included vaccine-specific concerns, a need for more information, antivaccine attitudes or beliefs, and a lack of trust. Limitations Participants' intent to be vaccinated was explored before a vaccine was available and when the pandemic was affecting a narrower swath of the United States. Questions about specific information or factors that might increase vaccination acceptance were not included. The survey response rate was 16.1%. Conclusion This national survey, conducted during the coronavirus pandemic, revealed that approximately 3 in 10 adults were not sure they would accept vaccination and 1 in 10 did not intend to be vaccinated against COVID-19. Targeted and multipronged efforts will be needed to increase acceptance of a COVID-19 vaccine when one becomes available. Primary funding source Agency for Healthcare Research and Quality.