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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Effects of Spaceflight Relevant Carbon Dioxide Levels on Pathogenesis Related Microbial Characteristics

BACKGROUND Multiple stressors in the spaceflight environment have the potential to alter microbial pathogenesis and virulence characteristics, including microgravity, radiation, and hostile/confined conditions. This combination of factors may lead to a stacking of risks, potentially creating unexpected increase in the risk of infectious disease. One understudied variable is the higher CO2 atmospheric concentration. The current Spaceflight Maximum Allowance Concentration (SMAC) for 24-hour average CO2 is 0.4% (3 mm Hg). These elevated ambient CO2 levels aboard the ISS could potentially influence the diversity and phenotypic responses of the resident microbial communities from both the spacecraft environment (air, surface, water) and crewmembers (gut, nasal, skin microbiomes). METHODS For these studies, we will evaluate the response of Staphylococcus aureus, Streptococcus pneumoniae and Enterobacter aerogenes, which are opportunistic pathogens that are of medical significance and have been or are likely to be found aboard spacecraft. These microorganisms will be cultured in both spaceflight analog and control conditions at CO2levels representing terrestrial atmospheric concentration of 0.04% (0.3 mmHg), ISS elevated concentration of 0.4% (3 mm Hg), and an unexpected elevated concentration of 1 % (7.6 mmHg) to represent a worst case scenario. DISCUSSION Overwhelming evidence from studies performed in food microbiology, marine biology and terrestrial environmental biology suggest altered gene expression, selective bacterial inhibition, increased growth and diversity, and increased antibiotic resistance of bacterial communities individually and in biofilm formation when exposed to increased levels of CO2. While many of these findings are based on levels of CO2 higher than would be found during spaceflight exploration missions, the potential for subtle changes in CO2 levels to exacerbate infectious disease risks warrants an evaluation of pathogen responses to spaceflight CO2 conditions. Our study will provide answers to spaceflight relevant atmospheric conditions, as described in the Risk of Adverse Health Effects Due to Host-Microorganism Interaction (GapMicro 103).

A A Medina-Colorado↗
NASA NTRSDate not supplied

Effects of Spaceflight Relevant Carbon Dioxide Levels on Pathogenesis Related Microbial Characteristics

Multiple stressors in the spaceflight environment, including microgravity and radiation, have the potential to alter microbial pathogenesis and virulence characteristics. Understanding how these and other factors may exacerbate the risk of infectious disease for astronauts is important to ensure the success of the mission. One understudied question in our assessment of infectious disease risk is the contribution carbon dioxide (CO2) at atmospheric concentrations higher than would be observed in terrestrial settings. Previous terrestrial studies have shown altered gene expression, selective bacterial inhibition, increased growth and diversity, and increased antibiotic resistance of bacterial communities individually and in biofilms when exposed to increased levels of CO2. While many of these findings are based on levels of CO2 higher than would be found during spaceflight exploration missions, the potential for subtle changes in CO2 levels to exacerbate infectious disease risks warrants an evaluation of pathogen responses to spaceflight CO2 conditions. To address this question, we are evaluating the effects of elevated atmospheric CO2 on microbial concentration, diversity, and pathogenesis-related characteristics using medically significant microorganisms cultured at CO2 levels representing terrestrial atmospheric concentration (≈0.04 %), ISS elevated concentration (0.4 %), and an unexpectedly elevated concentration (1 %) to represent a worst-case scenario. To determine if microbial responses to these CO2 concentrations may be exacerbated in response to the spaceflight environment, microorganisms are being cultured under static conditions and both spaceflight analogue and control conditions using the Rotating Wall Vessel (RWV) bioreactor (Synthecon, Houston, TX). For these studies, we will evaluate the response of Staphylococcus aureus, Streptococcus pneumoniae, and Enterobacter aerogenes, which are opportunistic bacterial pathogens that are of medical significance and have been or are likely to be found aboard human-inhabited spacecraft. Bacteria will be evaluated individually and together as a consortium. The following Specific Aims are be investigated: Aim 1. Characterize the growth, diversity, and pathogenesis-related stress responses of medically significant microorganisms grown under multiple CO2 concentrations under static growth in a liquid medium. Stress responses include acid stress, oxidative stress, and thermal stress. Aim 2. Characterize the growth, diversity, and pathogenesis-related stress responses of medically significant microorganisms grown under multiple CO2 concentrations in both spaceflight analogue and control conditions. Stress responses include acid stress, oxidative stress, and thermal stress.

S G Thornhill↗
NASA NTRSDate not supplied

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗
NASA NTRSDate not supplied

Development of Machine Learning-Derived Microbiological and Immune Signatures: Applications in Adaptive Risk Assessment of Infectious Disease During Spaceflight

Infectious diseases represent an urgent risk for spaceflight with consequences ranging from loss in crew performance to crew incapacitation or loss of life should an outbreak occur. The resident environmental microbiome on the International Space Station has been monitored through routine surveillance over almost twenty years, beginning with culture-based microbial detection which has advanced to molecular methods in recent years. This has created a wealth of data that we have begun mining to define the microbial ecology of the ISS. Summarized here is our analysis of data from the historical microbial population defined by culture-based monitoring from the past two decades, organized by their likelihood to cause disease into clinical categories. As expected, many residents of the normal microflora in environments where people work and live were detected. However, some known pathogens were also detected. As the spaceflight environment can predispose humans to infection, crew health records were used to source additional data for the set to uncover clinical relevance. Data mining was performed on crew health records to capture adverse health events that may be related to infectious disease. Machine learning, specifically Random Forest analysis, was used to analyze the microbial and crew health datasets. The symptom categories were not explained by the ranked bacteria, due to lack of sufficient data for some categories and due to poor ranking of the pathogens for others. Poor ranking of the bacteria could be due to the clinical symptoms being linked to other disease-causing factors, such as allergy or viral infection. These findings suggest a lack of relationship between bacteria detected on surfaces in the ISS and historical health events experienced by astronauts.

Kristyn Hoffman↗
NASA NTRS2025

The Microbiome of A Tomato Crop Grown Under Different Lighting Regimes on the International Space Station

The VEG-05 experiment presented here investigated the effect of red-rich and blue-rich light recipes in Veggie on the microbiome of the Veggie facility and the plant tissues of a dwarf tomato variety, Solanum lycopersicum cv. Red Robin. For food safety, the plants were screened using culture-based methods for potential human pathogens that may cause infection by consumption of the fruit. The microbiome was investigated using bacterial 16S and fungal ITS sequencing methods to enumerate and identify bacterial and fungal communities on tomato fruit, roots, leaves, rooting substrate, and Veggie facility surfaces grown under blue-rich or red-rich lighting. Comparisons of microbial communities were made between lighting treatments, as well as for flight and ground controls. This analysis determined the core microbiome and microbiological composition for tomato plants grown under a blue-rich or red-rich lighting treatment and microgravity conditions. Culture-based pathogen screening, corroborated by 16S and ITS sequencing, yielded negative results. Bacterial and fungal counts were lower for ground controls than in-flight samples. However, there were no differences in microbial counts between lighting treatments. Regardless of lighting treatment, plant components shared a core microbiome, although some differences were observed in genera between lighting treatments.

Veggie↗
DOE OSTI2012

Method for concentration and separation of biological organisms by ultrafiltration and dielectrophoresis

Disclosed is a method for monitoring sources of public water supply for a variety of pathogens by using a combination of ultrafiltration techniques together dielectrophoretic separation techniques. Because water-borne pathogens, whether present due to "natural" contamination or intentional introduction, would likely be present in drinking water at low concentrations when samples are collected for monitoring or outbreak investigations, an approach is needed to quickly and efficiently concentrate and separate particles such as viruses, bacteria, and parasites in large volumes of water (e.g., 100 L or more) while simultaneously reducing the sample volume to levels sufficient for detecting low concentrations of microbes (e.g., <10 mL). The technique is also designed to screen the separated microbes based on specific conductivity and size.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

The Ecological Genomics of Fungi: Repeated Elements in Filamentous Fungi with a Focus on Wood-Decay Fungi

In the last decade, the genome of several dozen filamentous fungi have been sequenced. Interestingly, vast diversity in genome size was observed (Fig. 2.1) with 14-fold differences between the 9 Mb of the human pathogenic dandruff fungus (Malassezia globosa; Xu, Saunders, et al., 2007) and the 125 Mb of the ectomycorrhizal black truffle of P rigord (Tuber melanosporum; Martin, Kohler, et al., 2010). Recently, Raffaele and Kamoun (2012) highlighted that the genomes of several lineages of filamentous plant pathogens have been shaped by repeat-driven expansion. Indeed, repeated elements are ubiquitous in all prokaryote and eukaryote genomes; however, their frequencies can vary from just a minor percentage of the genome to more that 60 percent of the genome. Repeated elements can be classified in two major types: satellites DNA and transposable elements. In this chapter, the different types of repeated elements and how these elements can impact genome and gene repertoire will be described. Also, an intriguing link between the transposable elements richness and diversity and the ecological niche will be highlighted.

Murat, Claude↗
DOE OSTI2014

Disposable and removable nucleic acid extraction and purification cartridges for automated flow-through systems

Removable cartridges are used on automated flow-through systems for the purpose of extracting and purifying genetic material from complex matrices. Different types of cartridges are paired with specific automated protocols to concentrate, extract, and purifying pathogenic or human genetic material. Their flow-through nature allows large quantities sample to be processed. Matrices may be filtered using size exclusion and/or affinity filters to concentrate the pathogen of interest. Lysed material is ultimately passed through a filter to remove the insoluble material before the soluble genetic material is delivered past a silica-like membrane that binds the genetic material, where it is washed, dried, and eluted. Cartridges are inserted into the housing areas of flow-through automated instruments, which are equipped with sensors to ensure proper placement and usage of the cartridges. Properly inserted cartridges create fluid- and air-tight seals with the flow lines of an automated instrument.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Detecting anthrax in the palm of your hand: applications of a smartphone microscope

Bacillus anthracis is a bacterial pathogen that causes the disease anthrax. In 2001, B. anthracis was used in a bioterrorism attack in the United States that resulted in 22 individuals becoming infected, 5 of whom died as a result of this attack. A great deal of attention has been dedicated to responding to bioterrorism events to reduce the potential loss of lives. One such area of research has focused on the development of new technologies to detect and respond to the intentional release of bacterial pathogens such as B. anthracis.

B. anthracis, anthrax, smartphone microscope, fluo↗
DOE OSTI2013

Rapid Threat Organism Recognition Pipeline

The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on quality and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.

Williams, Kelly P.↗
DOE OSTI2015

Genetic Control of Plant Root Colonization by the Biocontrol agent, Pseudomonas fluorescens

Plant growth promoting rhizobacteria (PGPR) are a critical component of plant root ecosystems. PGPR promote plant growth by solubilizing inaccessible minerals, suppressing pathogenic microorganisms in the soil, and directly stimulating growth through hormone synthesis. Pseudomonas fluorescens is a well-established PGPR isolated from wheat roots that can also colonize the root system of the model plant, Arabidopsis thaliana. We have created barcoded transposon insertion mutant libraries suitable for genome-wide transposon-mediated mutagenesis followed by sequencing (TnSeq). These libraries consist of over 105 independent insertions, collectively providing loss-of-function mutants for nearly all genes in the P.fluorescens genome. Each insertion mutant can be unambiguously identified by a randomized 20 nucleotide sequence (barcode) engineered into the transposon sequence. We used these libraries in a gnotobiotic assay to examine the colonization ability of P.fluorescens on A.thaliana roots. Taking advantage of the ability to distinguish individual colonization events using barcode sequences, we assessed the timing and microbial concentration dependence of colonization of the rhizoplane niche. These data provide direct insight into the dynamics of plant root colonization in an in vivo system and define baseline parameters for the systematic identification of the bacterial genes and molecular pathways using TnSeq assays. Having determined parameters that facilitate potential colonization of roots by thousands of independent insertion mutants in a single assay, we are currently establishing a genome-wide functional map of genes required for root colonization in P.fluorescens. Importantly, the approach developed and optimized here for P.fluorescens>A.thaliana colonization will be applicable to a wide range of plant-microbe interactions, including biofuel feedstock plants and microbes known or hypothesized to impact on biofuel-relevant traits including biomass productivity and pathogen resistance.

Cole, Benjamin J.↗
DOE OSTI2014

Exploring Arabidopsis thaliana Root Endophytes via Single-Cell Genomics

Land plants grow in association with microbial communities both on their surfaces and inside the plant (endophytes). The relationships between microbes and their host can vary from pathogenic to mutualistic. Colonization of the endophyte compartment occurs in the presence of a sophisticated plant immune system, implying finely tuned discrimination of pathogens from mutualists and commensals. Despite the importance of the microbiome to the plant, relatively little is known about the specific interactions between plants and microbes, especially in the case of endophytes. The vast majority of microbes have not been grown in the lab, and thus one of the few ways of studying them is by examining their DNA. Although metagenomics is a powerful tool for examining microbial communities, its application to endophyte samples is technically difficult due to the presence of large amounts of host plant DNA in the sample. One method to address these difficulties is single-cell genomics where a single microbial cell is isolated from a sample, lysed, and its genome amplified by multiple displacement amplification (MDA) to produce enough DNA for genome sequencing. This produces a single-cell amplified genome (SAG). We have applied this technology to study the endophytic microbes in Arabidopsis thaliana roots. Extensive 16S gene profiling of the microbial communities in the roots of multiple inbred A. thaliana strains has identified 164 OTUs as being significantly enriched in all the root endophyte samples compared to their presence in bulk soil.

09 BIOMASS FUELS↗
DOE OSTI2018

Lake Arrowhead Microbial Genomics Conference

The Lake Arrowhead Microbial Genomics Conference (formerly the E. coli and Small Genomes Conference, and the Microbial Genomes Conference) was held September 16-20, 2018, at the UCLA Conference Center at Lake Arrowhead, California. This conference is part of a yearly meeting initiated in 1991 to bring together genome sequencers, bioinformatics specialists, biologists, and geneticists, to forge interactions that would result in meaningful functional genomics. The goal of the meeting was to translate the influx of new genome sequencing information into useful biological studies. The Lake Arrowhead 2018 meeting had a major focus on microbial communities, the human microbiome, pathogens, bioenergetics, and environmental microbiology. The field of genomics has reached the point where deriving the sequence of an organism’s entire genome is now seen as a beginning rather than an endpoint. Moreover, understanding the sequences of whole communities, and particularly those that make up different microbiomes, is now a central point of the field. The 2018 meeting covered microorganisms for which extensive analyses exist, and those for which new biological and technical strategies are being developed. The focus on biodiversity, the human microbiome, pathogenic organisms, and bioenergetics added special significance to this meeting. This meeting was designed to have a mix of 34 invited presentations and poster sessions with 80 posters, and had 160 participants. This meeting has become established as a major annual microbial genomics conference during the last 26 years and has assured status and quality. It offers a major opportunity for young investigators and students to attend, present posters, and give talks. In fact, 22 of the 34 invited speakers were early career stage scientists. An important impact of the conference was the forging of new collaborations between scientists and particularly young scientists with the array of multidisciplinary researchers at the meeting.

Miller, Jeffrey H.↗
DOE OSTI2021

Air Return Strategies and Airborne SARS-CoV-2

Dedicated ducted air return per zone for heating, ventilating, and air-conditioning (HVAC) systems is sometimes claimed to be a superior technique over plenum return strategy from the viewpoint of exposure reduction to airborne pathogens. While both the return strategies have advantages, there is limited evidence in the literature as to which strategy is superior merely from a standpoint of building vulnerability to airborne contaminants. We performed multizonal airborne contaminant dispersion modelling using CONTAM to simulate the overall building vulnerability to airborne SARS-CoV-2 aerosols when released in an office building and evaluated the two air return strategies. Results showed that for ducted returns, maintaining negative pressure in the release zone coupled with 100% outdoor air supply can greatly reduce overall building vulnerability. However, for a building maintained under a slight positive pressure and a recirculated air percentage as low as 31%, ducted returns do not necessarily outperform plenum returns in terms of overall building vulnerability to airborne pathogens. Building-specific details and factors that are not easily represented with multizone modelling are important, making general preferential statements for either strategy difficult to make. Insights from this study can guide new construction and retrofits of buildings both during and after the COVID-19 pandemic with the aim of safe re-occupancy of buildings while keeping the buildings resilient against potential future epidemics spread by airborne agents.

Shrestha, Prateek↗
DOE OSTI2022

Chapter 8: Agricultural Use

Biochar has potential to reduce the environmental footprint in nearly every aspect of agricultural production. The use of biochar has been proposed to manage agricultural biomass (reference), to process animal manure and poultry litter (reference), to improve the nutritive value of feed (reference), and to mitigate the offsite movement of pesticides (reference) and soil nutrients (reference). The coproducts of biochar production hold similar potential. For example, on farm production of biochar can provide bioenergy to heat greenhouses and barns and to power farm equipment (reference). Pyroligneous acid, a coproduct of pyrolysis, has the ability to control fungal pathogens and deter pathogenic insects (reference). Although these environmental benefits are potentially substantial, their on-farm use has not been widely studied. Furthermore, the on-farm installation of biochar production facilities presents challenges that reduce the feasibility of co-production scenarios (Phillips 2018). As such, this section primarily addresses the application of biochar to agricultural soils.

agriculture↗
DOE OSTI2022

Lake Arrowhead Microbial Genomics Conference

The Lake Arrowhead Microbial Genomics Conference (formerly the E. coli and Small Genomes Conference, and the Microbial Genomes Conference) was held September 11-15, 2022, at the UCLA Conference Center at Lake Arrowhead, California. This conference is part of a yearly meeting initiated in 1991 to bring together genome sequencers, bioinformatics specialists, biologists, and geneticists, to forge interactions that would result in meaningful functional genomics. The goal of the meeting was to translate the influx of new genome sequencing information into useful biological studies. The Lake Arrowhead 2022 meeting had a major focus on microbial communities, the human microbiome, pathogens, phage therapy, bioinformatic methods of analysis, bioenergenics, and environmental microbiology. The field of genomics has reached the point where deriving the sequence of an organism’s entire genome is now seen as a beginning rather than an endpoint. Moreover, understanding the sequences of whole communities, and particularly those that make up different microbiomes, is now a central point of the field. The 2022 meeting covered microorganisms for which extensive analyses exist, and those for which new biological and technical strategies are being developed. The focus on biodiversity, the human microbiome, pathogenic organisms and methods of countering them, and bioenergetics added special significance to this meeting. This meeting was designed to have a mix of 36 invited presentations and poster sessions with more than 80 posters, and had 147 participants. This meeting has become established as a major annual microbial genomics conference during the last 29 years and has assured status and quality. It offers a major opportunity for young investigators and students to attend, present posters, and give talks. In fact, 50% of the invited speakers were early career stage scientists. An important impact of the conference was the forging of new collaborations between scientists and particularly young scientists with the array of multidisciplinary researchers at the meeting.

Miller, Jeffrey H.↗
DOE OSTI2025

Exploring phage–host interactions in Burkholderia cepacia complex bacterium to reveal host factors and phage resistance genes using CRISPRi functional genomics and transcriptomics

Complex interactions of bacteriophages with their bacterial hosts determine phage host range and infectivity. While phage defense systems and host factors have been identified in model bacteria, they remain challenging to predict in non-model bacteria. In this paper, we integrate functional genomics and transcriptomics to investigate phage–host interactions, revealing active phage resistance and host factor genes in Burkholderia cenocepacia K56-2. Burkholderia cepacia complex species are commonly found in soil and are opportunistic pathogens in immunocompromised patients. We studied infection of B. cenocepacia K56-2 with Bcep176, a temperate phage isolated from Burkholderia multivorans. A genome-wide dCas9 knockdown library targeting B. cenocepacia K56-2 was constructed, and a pooled infection experiment identified 63 novel genes or operons coding for candidate host factors or phage resistance genes. The activities of a subset of candidate host factor and resistance genes were validated via single-gene knockdowns. Transcriptomics of B. cenocepacia K56-2 during Bcep176 infection revealed that expression of genes coding for host factor and resistance candidates identified in this screen was significantly altered during infection by 4 h post-infection. Identifying which bacterial genes are involved in phage infection is important to understand the ecological niches of B. cenocepacia and its phages, and for designing phage therapies.

Bacterial Pathogenesis↗
DOE OSTI2026

An improved dataset for predicting mammal infecting viruses from genetic sequence information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alternative data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 ± 0.070 to 0.784 ± 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 ± 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no better than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 ± 0.08) or not (ROC AUC 0.50 ± 0.04).

59 BASIC BIOLOGICAL SCIENCES↗