Environmental reservoirs of pathogenic mycobacteria across the Ethiopian biogeographical landscape

King, Hayley C.; Khera-Butler, Tanya; James, Phillip; Oakley, Brian B.; Erenso, Girume; Aseffa, Abraham; Knight, Rob; Wellington, Elizabeth M. H.; Courtenay, Orin

doi:10.1371/journal.pone.0173811

Cited by 42 publications

(29 citation statements)

References 40 publications

(32 reference statements)

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“…Another study showed that higher elevation correlated to increased NTM up to 4000 m, with water temperatures between 17-23°C (i.e. similar to Hawaiian waters), and that environmental correlations and NTM species diversity may vary locally (King et al, 2017). Although patients can be cured, they are often re-infected with the same or another NTM species (Lipner et al, 2017).…”

Section: Background On Ntmmentioning

confidence: 99%

GEOLOGICAL AND GEOCHEMICAL CONTROLS ON NON-TUBERCULOUS MYCOBACTERIUM TRANSMISSION: EXAMPLES FROM HAWAII

Robinson¹

2019

Geological Society of America Abstracts With Programs

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grant 1743587. I give many thanks to my committee (Drs. Steve Nelson, Barry Bickmore, Zach Aanderud, and Norm Jones), who made large contributions to the statistical methods, sampling strategies, groundwater model design, and critiques. Dr. Randy Larsen deserves credit for helping to create scientifically sound, logistic models. Josephine Hoh and Richard Pezzulo were a great help in granting access and providing escorted sampling trips in Waimea Valley. Kevin Rey and Kaleb Markert assisted through field and lab support. Dave Tingey must be acknowledged for his intellectual support in preparing samples for analysis and instruction. My best friend and wife, Kaylee, has been a great support and encouragement through both the hard and comfortable aspects of this thesis, for which, I am very grateful.

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Section: Background On Ntmmentioning

confidence: 99%

GEOLOGICAL AND GEOCHEMICAL CONTROLS ON NON-TUBERCULOUS MYCOBACTERIUM TRANSMISSION: EXAMPLES FROM HAWAII

Robinson¹

2019

Geological Society of America Abstracts With Programs

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“…The literature regarding microbial biogeography and community ecology has hitherto focused primarily on characterizing microbial populations on a "macro" scale-for instance, within non-spatially resolved environments such as soil and water [6][7][8]. Yet studies defining microbial consortia at various anatomical geographies now highlight the notion that microorganisms also display clear distribution patterns on this anatomical level, from site to site and tissue to tissue, varying in states of health and disease [9].…”

Section: Introductionmentioning

confidence: 99%

The Best of All Worlds: Streptococcus pneumoniae Conjunctivitis through the Lens of Community Ecology and Microbial Biogeography

et al. 2019

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The study of the forces which govern the geographical distributions of life is known as biogeography, a subject which has fascinated zoologists, botanists and ecologists for centuries. Advances in our understanding of community ecology and biogeography—supported by rapid improvements in next generation sequencing technology—have now made it possible to identify and explain where and why life exists as it does, including within the microbial world. In this review, we highlight how a unified model of microbial biogeography, one which incorporates the classic ecological principles of selection, diversification, dispersion and ecological drift, can be used to explain community dynamics in the settings of both health and disease. These concepts operate on a multiplicity of temporal and spatial scales, and together form a powerful lens through which to study microbial population structures even at the finest anatomical resolutions. When applied specifically to curious strains of conjunctivitis-causing, nonencapsulated Streptococcus pneumoniae, we show how this conceptual framework can be used to explain the possible evolutionary and disease-causing mechanisms which allowed these lineages to colonize and invade a separate biogeography. An intimate knowledge of this radical bifurcation in phylogeny, still the only known niche subspecialization for S. pneumoniae to date, is critical to understanding the pathogenesis of ocular surface infections, nature of host-pathogen interactions, and developing strategies to curb disease transmission.

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“…YCOBACTERIUM is a genus of Actinobacteria [1], which includes pathogens known to cause serious diseases in humans, such as Mycobacterium tuberculosis (Mtb) that causes global tuberculosis epidemic and accounts for more than 15 millions of deaths since 2000 [2]. Early and accurate detection of Mtb infection is an urgent need.…”

Section: Introductionmentioning

confidence: 99%

A novel deep learning scheme for morphology-based classification of mycobacterial infection in unstained macrophages

Zhao

Bao

Wang

et al. 2019

Preprint

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Objective: Mycobacterium tuberculosis (Mtb) is an airborne, contagious bacterial pathogen that causes widespread infections in humans. Using Mycobacterium marinum (Mm), a surrogate model organism for Mtb research, the present study develops a deep learning-based scheme that can classify the Mminfected and uninfected macrophages in tissue culture solely based on morphological changes. Methods: A novel weak-and semisupervised learning method is developed to detect and extract the cells, firstly. Then, transfer learning and fine-tuning from the CNN is built to classify the infected and uninfected cells. Results: The performance is evaluated by accuracy (ACC), sensitivity (SENS) and specificity (SPEC) with 10-fold cross-validation. It demonstrates that the scheme can classify the infected cells accurately and efficiently at the early infection stage. At 2 hour post infection (hpi), we achieve the ACC of 0.923 ± 0.005, SENS of 0.938 ± 0.020, and SPEC of 0.905 ± 0.019, indicating that the scheme has detected significant morphological differences between the infected and uninfected macrophages, although these differences are hardly visible to naked eyes. Interestingly, the ACC at 12 and 24 hpi are 0.749 ± 0.010 and 0.824 ± 0.009, respectively, suggesting that the infection-induced morphological changes are dynamic throughout the infection. Finally, deconvolution with guided propagation maps the key morphological features contributing to the classification. Significance: This proof-ofconcept study provides a novel venue to investigate bacterial pathogenesis in a macroscopic level and has a great promise in diagnosis of bacterial infections.

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Environmental reservoirs of pathogenic mycobacteria across the Ethiopian biogeographical landscape

Cited by 42 publications

References 40 publications

GEOLOGICAL AND GEOCHEMICAL CONTROLS ON NON-TUBERCULOUS MYCOBACTERIUM TRANSMISSION: EXAMPLES FROM HAWAII

GEOLOGICAL AND GEOCHEMICAL CONTROLS ON NON-TUBERCULOUS MYCOBACTERIUM TRANSMISSION: EXAMPLES FROM HAWAII

The Best of All Worlds: Streptococcus pneumoniae Conjunctivitis through the Lens of Community Ecology and Microbial Biogeography

A novel deep learning scheme for morphology-based classification of mycobacterial infection in unstained macrophages

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