Categorizing Sequences of Concern by Function To Better Assess Mechanisms of Microbial Pathogenesis

Godbold, Gene D.; Kappell, Anthony D.; LeSassier, Danielle S.; Treangen, Todd J.; Ternus, Krista

doi:10.1128/iai.00334-21

Cited by 10 publications

(14 citation statements)

References 298 publications

(372 reference statements)

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“…Taken together, current databases do not serve the purpose needed for biohazard identification necessitating the need for better definition and curation around hazardous functions. Godbold et al recently described a controlled vocabulary called Functions of Sequences of Concern microbial pathogenesis research for bioinformatic applications (Godbold GD et al, 2021). Here we demonstrate the utility of these types of sequences of concern for understanding biohazards associated with bioengineering functional building blocks.…”

Section: Introductionmentioning

confidence: 62%

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments

Gemler

Mukherjee

Howland

et al. 2022

Front. Bioeng. Biotechnol.

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Bioengineering applies analytical and engineering principles to identify functional biological building blocks for biotechnology applications. While these building blocks are leveraged to improve the human condition, the lack of simplistic, machine-readable definition of biohazards at the function level is creating a gap for biosafety practices. More specifically, traditional safety practices focus on the biohazards of known pathogens at the organism-level and may not accurately consider novel biodesigns with engineered functionalities at the genetic component-level. This gap is motivating the need for a paradigm shift from organism-centric procedures to function-centric biohazard identification and classification practices. To address this challenge, we present a novel methodology for classifying biohazards at the individual sequence level, which we then compiled to distinguish the biohazardous property of pathogenicity at the whole genome level. Our methodology is rooted in compilation of hazardous functions, defined as a set of sequences and associated metadata that describe coarse-level functions associated with pathogens (e.g., adherence, immune subversion). We demonstrate that the resulting database can be used to develop hazardous “fingerprints” based on the functional metadata categories. We verified that these hazardous functions are found at higher levels in pathogens compared to non-pathogens, and hierarchical clustering of the fingerprints can distinguish between these two groups. The methodology presented here defines the hazardous functions associated with bioengineering functional building blocks at the sequence level, which provide a foundational framework for classifying biological hazards at the organism level, thus leading to the improvement and standardization of current biosecurity and biosafety practices.

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Section: Introductionmentioning

confidence: 62%

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments

Gemler

Mukherjee

Howland

et al. 2022

Front. Bioeng. Biotechnol.

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“…These may not be well-defined taxonomically [ 4 ] since sequences with similar taxonomic labels can contain mostly non-pathogenic sequences with a smattering of pathogenic ones. Even at the strain level, addition or subtraction of a single gene may affect the overall pathogenicity of the microbe [ 60 ]. SeqScreen provides a novel approach to this important problem and focuses on read-level analyses that facilitate the detection of low abundance pathogenic sequences from metagenomic samples.…”

Section: Discussionmentioning

confidence: 99%

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning

et al. 2022

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The COVID-19 pandemic has emphasized the importance of accurate detection of known and emerging pathogens. However, robust characterization of pathogenic sequences remains an open challenge. To address this need we developed SeqScreen, which accurately characterizes short nucleotide sequences using taxonomic and functional labels and a customized set of curated Functions of Sequences of Concern (FunSoCs) specific to microbial pathogenesis. We show our ensemble machine learning model can label protein-coding sequences with FunSoCs with high recall and precision. SeqScreen is a step towards a novel paradigm of functionally informed synthetic DNA screening and pathogen characterization, available for download at www.gitlab.com/treangenlab/seqscreen.

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“…Although this experiment was focused on the impact of COVID-19 disease on the BALF microbiome, none of the methods employed in this study were specific to COVID-19. We hope that the methods implemented here will be useful to the research community for other microbiome and pathogen-related association experiments, particularly as more metatranscriptome sequences and pathogenesis gene ontologies are created in the future 52 , 53 .…”

Section: Discussionmentioning

confidence: 99%

Analysis of bronchoalveolar lavage fluid metatranscriptomes among patients with COVID-19 disease

Jochum

Lee

Curry

et al. 2022

Sci Rep

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To better understand the potential relationship between COVID-19 disease and hologenome microbial community dynamics and functional profiles, we conducted a multivariate taxonomic and functional microbiome comparison of publicly available human bronchoalveolar lavage fluid (BALF) metatranscriptome samples amongst COVID-19 (n = 32), community acquired pneumonia (CAP) (n = 25), and uninfected samples (n = 29). We then performed a stratified analysis based on mortality amongst the COVID-19 cohort with known outcomes of deceased (n = 10) versus survived (n = 15). Our overarching hypothesis was that there are detectable and functionally significant relationships between BALF microbial metatranscriptomes and the severity of COVID-19 disease onset and progression. We observed 34 functionally discriminant gene ontology (GO) terms in COVID-19 disease compared to the CAP and uninfected cohorts, and 21 GO terms functionally discriminant to COVID-19 mortality (q < 0.05). GO terms enriched in the COVID-19 disease cohort included hydrolase activity, and significant GO terms under the parental terms of biological regulation, viral process, and interspecies interaction between organisms. Notable GO terms associated with COVID-19 mortality included nucleobase-containing compound biosynthetic process, organonitrogen compound catabolic process, pyrimidine-containing compound biosynthetic process, and DNA recombination, RNA binding, magnesium and zinc ion binding, oxidoreductase activity, and endopeptidase activity. A Dirichlet multinomial mixtures clustering analysis resulted in a best model fit using three distinct clusters that were significantly associated with COVID-19 disease and mortality. We additionally observed discriminant taxonomic differences associated with COVID-19 disease and mortality in the genus Sphingomonas, belonging to the Sphingomonadacae family, Variovorax, belonging to the Comamonadaceae family, and in the class Bacteroidia, belonging to the order Bacteroidales. To our knowledge, this is the first study to evaluate significant differences in taxonomic and functional signatures between BALF metatranscriptomes from COVID-19, CAP, and uninfected cohorts, as well as associating these taxa and microbial gene functions with COVID-19 mortality. Collectively, while this data does not speak to causality nor directionality of the association, it does demonstrate a significant relationship between the human microbiome and COVID-19. The results from this study have rendered testable hypotheses that warrant further investigation to better understand the causality and directionality of host–microbiome–pathogen interactions.

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Categorizing Sequences of Concern by Function To Better Assess Mechanisms of Microbial Pathogenesis

Cited by 10 publications

References 298 publications

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning

Analysis of bronchoalveolar lavage fluid metatranscriptomes among patients with COVID-19 disease

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