Host gut resistome in Gulf War chronic multisymptom illness correlates with persistent inflammation

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Abstract

Chronic multisymptom illness (CMI) affects a subsection of elderly and war Veterans and is associated with systemic inflammation. Here, using a mouse model of CMI and a group of Gulf War (GW) Veterans’ with CMI we show the presence of an altered host resistome. Results show that antibiotic resistance genes (ARGs) are significantly altered in the CMI group in both mice and GW Veterans when compared to control. Fecal samples from GW Veterans with persistent CMI show a significant increase of resistance to a wide class of antibiotics and exhibited an array of mobile genetic elements (MGEs) distinct from normal healthy controls. The altered resistome and gene signature is correlated with mouse serum IL-6 levels. Altered resistome in mice also is correlated strongly with intestinal inflammation, decreased synaptic plasticity, reversible with fecal microbiota transplant (FMT). The results reported might help in understanding the risks to treating hospital acquired infections in this population.

Abstract

Analysis of fecal samples from patients and mice, shows that chronic multisymptom illness which affects a subsection of elderly and war Veterans, is associated with alteration in genes related to antibiotic resistance.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

Daniel J. Buysse, Charles Reynolds III, Timothy H Monk … (1989)

Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.

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Prodigal: prokaryotic gene recognition and translation initiation site identification

Doug Hyatt, Gwo-Liang Chen, Philip LoCascio … (2010)

Background The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals. Results With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives. Conclusion We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.

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Author and article information

Contributors

Saurabh Chatterjee:

ORCID: http://orcid.org/0000-0003-1649-7149

schatt@mailbox.sc.edu

Journal

Journal ID (nlm-ta): Commun Biol

Journal ID (iso-abbrev): Commun Biol

Title: Communications Biology

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2399-3642

Publication date (Electronic): 7 June 2022

Publication date PMC-release: 7 June 2022

Publication date Collection: 2022

Volume: 5

Electronic Location Identifier: 552

Affiliations

[1 ]GRID grid.254567.7, ISNI 0000 0000 9075 106X, Environmental Health and Disease Laboratory, Department of Environmental Health Sciences, Arnold School of Public Health, , University of South Carolina, ; Columbia, SC USA

[2 ]GRID grid.254567.7, ISNI 0000 0000 9075 106X, Department of Chemistry and Biochemistry, , University of South Carolina, ; Columbia, SC USA

[3 ]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Department of Environmental Health, , Boston University School of Public Health, ; Boston, MA USA

[4 ]GRID grid.261241.2, ISNI 0000 0001 2168 8324, Department of Clinical Immunology, , Nova Southeastern University, ; Fort Lauderdale, FL USA

[5 ]GRID grid.430852.8, ISNI 0000 0001 0741 4132, Department of Cancer Biology and Pharmacology, , University of Illinois College of Medicine, ; Peoria, IL USA

[6 ]GRID grid.417149.e, ISNI 0000 0004 0420 4326, Columbia VA Medical Center, ; Columbia, SC USA

Author information

Punnag Saha http://orcid.org/0000-0001-6173-9798

Alan W. Decho http://orcid.org/0000-0002-2870-1824

Jie Li http://orcid.org/0000-0001-7977-6749

Saurabh Chatterjee http://orcid.org/0000-0003-1649-7149

Article

Publisher ID: 3494

DOI: 10.1038/s42003-022-03494-7

PMC ID: 9174162

PubMed ID: 35672382

SO-VID: d9b91d2a-8bd0-4f78-82c9-77423f456b7e

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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 14 June 2021

Date accepted : 17 May 2022

Funding

Funded by: FundRef https://doi.org/10.13039/100000005, U.S. Department of Defense (United States Department of Defense);

Award ID: W81XWH-13-2-0072

Award ID: W81XWH1810374

Award Recipient : Kimberly Sullivan Saurabh Chatterjee

Funded by: FundRef https://doi.org/10.13039/100000153, NSF | BIO | Division of Biological Infrastructure (DBI);

Award ID: OIA-1655740

Award Recipient : Jie Li

Funded by: FundRef https://doi.org/10.13039/100000738, U.S. Department of Veterans Affairs (Department of Veterans Affairs);

Award ID: I01CX001923-01

Award Recipient : Saurabh Chatterjee

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Keywords: translational research,microbiota

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Keywords: translational research, microbiota

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Host gut resistome in Gulf War chronic multisymptom illness correlates with persistent inflammation

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Microbiota and Host

Most cited references 79

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

Prodigal: prokaryotic gene recognition and translation initiation site identification

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