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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Mechanistic Model of Rothia mucilaginosa Adaptation toward Persistence in the CF Lung, Based on a Genome Reconstructed from Metagenomic Data

The impaired mucociliary clearance in individuals with Cystic Fibrosis (CF) enables opportunistic pathogens to colonize CF lungs. Here we show that Rothia mucilaginosa is a common CF opportunist that was present in 83% of our patient cohort, almost as prevalent as Pseudomonas aeruginosa (89%). Sequencing of lung microbial metagenomes identified unique R. mucilaginosa strains in each patient, presumably due to evolution within the lung. The de novo assembly of a near-complete R. mucilaginosa (CF1E) genome illuminated a number of potential physiological adaptations to the CF lung, including antibiotic resistance, utilization of extracellular lactate, and modification of the type I restriction-modification system. Metabolic characteristics predicted from the metagenomes suggested R. mucilaginosa have adapted to live within the microaerophilic surface of the mucus layer in CF lungs. The results also highlight the remarkable evolutionary and ecological similarities of many CF pathogens; further examination of these similarities has the potential to guide patient care and treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

ClassyFlu: Classification of Influenza A Viruses with Discriminatively Trained Profile-HMMs

Accurate and rapid characterization of influenza A virus (IAV) hemagglutinin (HA) and neuraminidase (NA) sequences with respect to subtype and clade is at the basis of extended diagnostic services and implicit to molecular epidemiologic studies. ClassyFlu is a new tool and web service for the classification of IAV sequences of the HA and NA gene into subtypes and phylogenetic clades using discriminatively trained profile hidden Markov models (HMMs), one for each subtype or clade. ClassyFlu merely requires as input unaligned, full-length or partial HA or NA DNA sequences. It enables rapid and highly accurate assignment of HA sequences to subtypes H1–H17 but particularly focusses on the finer grained assignment of sequences of highly pathogenic avian influenza viruses of subtype H5N1 according to the cladistics proposed by the H5N1 Evolution Working Group. NA sequences are classified into subtypes N1–N10. ClassyFlu was compared to semiautomatic classification approaches using BLAST and phylogenetics and additionally for H5 sequences to the new ‘‘Highly Pathogenic H5N1 Clade Classification Tool’’ (IRD-CT) proposed by the Influenza Research Database. Our results show that both web tools (ClassyFlu and IRD-CT), although based on different methods, are nearly equivalent in performance and both are more accurate and faster than semiautomatic classification. A retraining of ClassyFlu to altered cladistics as well as an extension of ClassyFlu to other IAV genome segments or fragments thereof is undemanding. This is exemplified by unambiguous assignment to a distinct cluster within subtype H7 of sequences of H7N9 viruses which emerged in China early in 2013 and caused more than 130 human infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

LABEL: Fast and Accurate Lineage Assignment with Assessment of H5N1 and H9N2 Influenza A Hemagglutinins

The evolutionary classification of influenza genes into lineages is a first step in understanding their molecular epidemiology and can inform the subsequent implementation of control measures. We introduce a novel approach called Lineage Assignment By Extended Learning (LABEL) to rapidly determine cladistic information for any number of genes without the need for time-consuming sequence alignment, phylogenetic tree construction, or manual annotation. Instead, LABEL relies on hidden Markov model profiles and support vector machine training to hierarchically classify gene sequences by their similarity to pre-defined lineages. We assessed LABEL by analyzing the annotated hemagglutinin genes of highly pathogenic (H5N1) and low pathogenicity (H9N2) avian influenza A viruses. Using the WHO/FAO/OIE H5N1 evolution working group nomenclature, the LABEL pipeline quickly and accurately identified the H5 lineages of uncharacterized sequences. Moreover, we developed an updated clade nomenclature for the H9 hemagglutinin gene and show a similarly fast and reliable phylogenetic assessment with LABEL. While this study was focused on hemagglutinin sequences, LABEL could be applied to the analysis of any gene and shows great potential to guide molecular epidemiology activities, accelerate database annotation, and provide a data sorting tool for other large-scale bioinformatic studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Comparing bacterial community composition of healthy and dark spot-affected Siderastrea siderea in Florida and the Caribbean

Coral disease is one of the major causes of reef degradation. Dark Spot Syndrome (DSS) was described in the early 1990's as brown or purple amorphous areas of tissue on a coral and has since become one of the most prevalent diseases reported on Caribbean reefs. It has been identified in a number of coral species, but there is debate as to whether it is in fact the same disease in different corals. Further, it is questioned whether these macroscopic signs are in fact diagnostic of an infectious disease at all. The most commonly affected species in the Caribbean is the massive starlet coral Siderastrea siderea . We sampled this species in two locations, Dry Tortugas National Park and Virgin Islands National Park. Tissue biopsies were collected from both healthy colonies and those with dark spot lesions. Microbial-community DNA was extracted from coral samples (mucus, tissue, and skeleton), amplified using bacterial-specific primers, and applied to PhyloChip G3 microarrays to examine the bacterial diversity associated with this coral. Samples were also screened for the presence of a fungal ribotype that has recently been implicated as a causative agent of DSS in another coral species, but the amplifications were unsuccessful. S. siderea samples did not cluster consistently based on health state (i.e., normal versus dark spot). Various bacteria, including Cyanobacteria and Vibrios , were observed to have increased relative abundance in the discolored tissue, but the patterns were not consistent across all DSS samples. Overall, our findings do not support the hypothesis that DSS in S. siderea is linked to a bacterial pathogen or pathogens. This dataset provides the most comprehensive overview to date of the bacterial community associated with the scleractinian coral S. siderea .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Microbiomes of commercially-available pine nuts and sesame seeds

Metagenomic analysis of food is becoming more routine and can provide important information pertaining to the shelf life potential and the safety of these products. However, less information is available on the microbiomes associated with low water activity foods. Pine nuts and sesame seeds, and food products which contain these ingredients, have been associated with recalls due to contamination with bacterial foodborne pathogens. The objective of this study was to identify the microbial community of pine nuts and sesame seeds using targeted 16S rRNA sequencing technology. Ten different brands of each seed type were assessed, and core microbiomes were determined. A total of 21 and 16 unique taxa with proportional abundances >1% in at least one brand were identified in the pine nuts and sesame seeds, respectively. Members of the core pine nut microbiome included the genera Alishewanella, Aminivibrio, Mycoplasma, Streptococcus, and unassigned OTUs in the families of Desulfobacteraceae and Xanthomonadaceae. For sesame seeds, the core microbiome included Aminivibrio, Chryseolina, Okibacterium, and unassigned OTUs in the family Flavobacteriaceae. The microbiomes of these seeds revealed that these products are dominated by environmental bacterial genera commonly isolated from soil, water, and plants; bacterial genera containing species known as commensal organisms were also identified. Understanding these microbiomes can aid in the risk assessment of these products by identifying food spoilage potential and community members which may co-enrich with foodborne bacterial pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Kinetics of Coinfection with Influenza A Virus and Streptococcus pneumoniae

Secondary bacterial infections are a leading cause of illness and death during epidemic and pandemic influenza. Experimental studies suggest a lethal synergism between influenza and certain bacteria, particularly Streptococcus pneumoniae, but the precise processes involved are unclear. In this paper, to address the mechanisms and determine the influences of pathogen dose and strain on disease, we infected groups of mice with either the H1N1 subtype influenza A virus A/Puerto Rico/8/34 (PR8) or a version expressing the 1918 PB1-F2 protein (PR8-PB1-F2(1918)), followed seven days later with one of two S. pneumoniae strains, type 2 D39 or type 3 A66.1. We determined that, following bacterial infection, viral titers initially rebound and then decline slowly. Bacterial titers rapidly rise to high levels and remain elevated. We used a kinetic model to explore the coupled interactions and study the dominant controlling mechanisms. We hypothesize that viral titers rebound in the presence of bacteria due to enhanced viral release from infected cells, and that bacterial titers increase due to alveolar macrophage impairment. Dynamics are affected by initial bacterial dose but not by the expression of the influenza 1918 PB1-F2 protein. Finally, our model provides a framework to investigate pathogen interaction during coinfections and to uncover dynamical differences based on inoculum size and strain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Kinetics of Myeloid Dendritic Cell Trafficking and Activation: Impact on Progressive, Nonprogressive and Controlled SIV Infections

We assessed the role of myeloid dendritic cells (mDCs) in the outcome of SIV infection by comparing and contrasting their frequency, mobilization, phenotype, cytokine production and apoptosis in pathogenic (pigtailed macaques, PTMs), nonpathogenic (African green monkeys, AGMs) and controlled (rhesus macaques, RMs) SIVagmSab infection. Through the identification of recently replicating cells, we demonstrated that mDC mobilization from the bone marrow occurred in all species postinfection, being most prominent in RMs. Circulating mDCs were depleted with disease progression in PTMs, recovered to baseline values after the viral peak in AGMs, and significantly increased at the time of virus control in RMs. Rapid disease progression in PTMs was associated with low baseline levels and incomplete recovery of circulating mDCs during chronic infection. mDC recruitment to the intestine occurred in all pathogenic scenarios, but loss of mucosal mDCs was associated only with progressive infection. Sustained mDC immune activation occurred throughout infection in PTMs and was associated with increased bystander apoptosis in blood and intestine. Conversely, mDC activation occurred only during acute infection in nonprogressive and controlled infections. Postinfection, circulating mDCs rapidly became unresponsive to TLR7/8 stimulation in all species. Yet, stimulation with LPS, a bacterial product translocated in circulation only in SIV-infected PTMs, induced mDC hyperactivation, apoptosis and excessive production of proinflammatory cytokines. After infection, spontaneous production of proinflammatory cytokines by mucosal mDCs increased only in progressor PTMs. We thus propose that mDCs promote tolerance to SIV in the biological systems that lack intestinal dysfunction. In progressive infections, mDC loss and excessive activation of residual mDCs by SIV and additional stimuli, such as translocated microbial products, enhance generalized immune activation and inflammation. Our results thus provide a mechanistic basis for the role of mDCs in the pathogenesis of AIDS and elucidate the causes of mDC loss during progressive HIV/SIV infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Bacterial Effector Activates Jasmonate Signaling by Directly Targeting JAZ Transcriptional Repressors

Gram-negative bacterial pathogens deliver a variety of virulence proteins through the type III secretion system (T3SS) directly into the host cytoplasm. These type III secreted effectors (T3SEs) play an essential role in bacterial infection, mainly by targeting host immunity. However, the molecular basis of their functionalities remains largely enigmatic. Here, we show that the Pseudomonas syringae T3SE HopZ1a, a member of the widely distributed YopJ effector family, directly interacts with jasmonate ZIM-domain (JAZ) proteins through the conserved Jas domain in plant hosts. JAZs are transcription repressors of jasmonate (JA)-responsive genes and major components of the jasmonate receptor complex. Upon interaction, JAZs can be acetylated by HopZ1a through a putative acetyltransferase activity. Importantly, P. syringae producing the wild-type, but not a catalytic mutant of HopZ1a, promotes the degradation of HopZ1-interacting JAZs and activates JA signaling during bacterial infection. Furthermore, HopZ1a could partially rescue the virulence defect of a P. syringae mutant that lacks the production of coronatine, a JA-mimicking phytotoxin produced by a few P. syringae strains. These results highlight a novel example by which a bacterial effector directly manipulates the core regulators of phytohormone signaling to facilitate infection. The targeting of JAZ repressors by both coronatine toxin and HopZ1 effector suggests that the JA receptor complex is potentially a major hub of host targets for bacterial pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes

Host-associated microbial communities (microbiomes) play critical roles in human, animal, and plant health and development. However, interactions between the host, members of the microbiome, and invading pathogens are in most cases still poorly understood. Such interactions are multidimensional and can alter the taxonomic composition and/or the functional metabolic activities of the microbiome in response to disease or treatment conditions. For example, after 2 days of antibiotic treatment, the mouse gut microbiome is altered and more susceptible to invasion by the pathogen Clostridioides difficile. Studies of these multidimensional interactions have been fueled by the ability to use high-throughput sequencing of phylogenetic marker genes to profile microbial community composition and shotgun metagenomics to profile functional potential. However, many protein-coding genes predicted from metagenomes are not necessarily expressed under a given condition, and thus, it is difficult to assess the activities and functional interactions in microbial communities based on DNA sequencing data alone. The physiological and pathological processes expressed in these communities under specific conditions are better reflected by the abundances of transcripts or proteins. In this Pearl, we provide a brief introduction to metaproteomics, which is a tool for the large-scale analysis of proteins in microbiomes that allows researchers to address a diversity of questions related to functions and interactions in microbiomes. The term “metaproteomics” was first used in 2004 for “the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time”, and since then, a large array of metaproteomics approaches have been developed. Our objective in this Pearl is to highlight what we feel are 5 essential elements to be considered for a metaproteomics research campaign and to introduce nonexpert readers to the topic without going into too much technical detail.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Year 2 Final Report - Protein Function Prediction Platform (v.0.5)

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The microbicidal potential of visible blue light in clinical medicine and public health

Visible blue light of wavelengths in the 400–470 nm range has been observed to have microbicidal properties. A widely accepted hypothesis for the mechanism of microbial inactivation by visible blue light is that the light causes photoexcitation of either endogenous (present within the microbe) or, exogenous (present in the biological medium surrounding the microbe) photosensitizers such as porphyrins and flavins, which leads to the release of reactive oxygen species that subsequently manifests microbicidal activity. Some of the factors that have been observed to be associated with enhanced microbicidal action include increased duration of exposure, and either pre- or co-treatment with quinine hydrochloride. In case of bacteria, repetitive exposure to the blue light shows no significant evidence of resistance development. Additionally, visible blue light has exhibited the ability to inactivate fungal and viral pathogens and, multidrug-resistant bacteria as well as bacterial biofilms. Visible blue light has demonstrated efficacy in eliminating foodborne pathogens found on food surfaces and exposed surfaces in the food processing environment as well as in the decontamination of surfaces in the clinical environment to minimize the spread of nosocomial infections. We conclude from reviewing existing literature on the application of the blue light in clinical medicine and public health settings that this microbicidal light is emerging as a safer alternative to conventional ultraviolet light-based technologies in multiple settings. However, further comprehensive studies and thorough understanding of the mechanism of microbicidal action of this light in different scenarios is warranted to determine its place in human health and disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A meta-analysis of soil microbial biomass responses to forest disturbances

Climate warming is likely to increase the frequency and severity of forest disturbances, with uncertain consequences for soil microbial communities and their contribution to ecosystem C dynamics. To address this uncertainty, we conducted a meta-analysis of 139 published soil microbial responses to forest disturbances. These disturbances included abiotic (fire, harvesting, storm) and biotic (insect, pathogen) disturbances. We hypothesized that soil microbial biomass would decline following forest disturbances, but that abiotic disturbances would elicit greater reductions in microbial biomass than biotic disturbances. In support of this hypothesis, across all published studies, disturbances reduced soil microbial biomass by an average of 29.4%. However, microbial responses differed between abiotic and biotic disturbances. Microbial responses were significantly negative following fires, harvest, and storms (48.7, 19.1, and 41.7% reductions in microbial biomass, respectively). In contrast, changes in soil microbial biomass following insect infestation and pathogen-induced tree mortality were non-significant, although biotic disturbances were poorly represented in the literature. When measured separately, fungal and bacterial responses to disturbances mirrored the response of the microbial community as a whole. Changes in microbial abundance following disturbance were significantly positively correlated with changes in microbial respiration. We propose that the differential effect of abiotic and biotic disturbances on microbial biomass may be attributable to differences in soil disruption and organic C removal from forests among disturbance types. Altogether, these results suggest that abiotic forest disturbances may significantly decrease soil microbial abundance, with corresponding consequences for microbial respiration. Further studies are needed on the effect of biotic disturbances on forest soil microbial communities and soil C dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Genome-Wide Analysis of Corynespora cassiicola Leaf Fall Disease Putative Effectors

Corynespora cassiicola is an Ascomycetes fungus with a broad host range and diverse life styles. Mostly known as a necrotrophic plant pathogen, it has also been associated with rare cases of human infection. In the rubber tree, this fungus causes the Corynespora leaf fall (CLF) disease, which increasingly affects natural rubber production in Asia and Africa. It has also been found as an endophyte in South American rubber plantations where no CLF outbreak has yet occurred. The C. cassiicola species is genetically highly diverse, but no clear relationship has been evidenced between phylogenetic lineage and pathogenicity. Cassiicolin, a small glycosylated secreted protein effector, is thought to be involved in the necrotrophic interaction with the rubber tree but some virulent C. cassiicola isolates do not have a cassiicolin gene. This study set out to identify other putative effectors involved in CLF. The genome of a highly virulent C. cassiicola isolate from the rubber tree (CCP) was sequenced and assembled. In silico prediction revealed 2870 putative effectors, comprising CAZymes, lipases, peptidases, secreted proteins and enzymes associated with secondary metabolism. Comparison with the genomes of 44 other fungal species, focusing on effector content, revealed a striking proximity with phylogenetically unrelated species ( Colletotrichum acutatum , Colletotrichum gloesporioides , Fusarium oxysporum , nectria hematococca , and Botrosphaeria dothidea ) sharing life style plasticity and broad host range. Candidate effectors involved in the compatible interaction with the rubber tree were identified by transcriptomic analysis. Differentially expressed genes included 92 putative effectors, among which cassiicolin and two other secreted singleton proteins. Finally, the genomes of 35 C. cassiicola isolates representing the genetic diversity of the species were sequenced and assembled, and putative effectors identified. At the intraspecific level, effector-based classification was found to be highly consistent with the phylogenomic trees. Identification of lineage-specific effectors is a key step toward understanding C. cassiicola virulence and host specialization mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

NEAr Transporter (NEAT) Domains: Unique Surface Displayed Heme Chaperones That Enable Gram-Positive Bacteria to Capture Heme-Iron From Hemoglobin

Iron is an important micronutrient that is required by bacteria to proliferate and to cause disease. Many bacterial pathogens forage iron from human hemoglobin (Hb) during infections, which contains this metal within heme (iron–protoporphyrin IX). Several clinically important pathogenic species within the Firmicutes phylum scavenge heme using surface-displayed or secreted NEAr Transporter (NEAT) domains. In this review, we discuss how these versatile proteins function in the Staphylococcus aureus Iron-regulated surface determinant system that scavenges heme-iron from Hb. S. aureus NEAT domains function as either Hb receptors or as heme-binding chaperones. In vitro studies have shown that heme-binding NEAT domains can rapidly exchange heme amongst one another via transiently forming transfer complexes, leading to the interesting hypothesis that they may form a protein-wire within the peptidoglycan layer through which heme flows from the microbial surface to the membrane. In Hb receptors, recent studies have revealed how dedicated heme- and Hb-binding NEAT domains function synergistically to extract Hb’s heme molecules, and how receptor binding to the Hb-haptoglobin complex may block its clearance by macrophages, prolonging microbial access to Hb’s iron. The functions of NEAT domains in other Gram-positive bacteria are also reviewed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Sequencing the Genomes of the First Terrestrial Fungal Lineages: What Have We Learned?

The first genome sequenced of a eukaryotic organism was for Saccharomyces cerevisiae, as reported in 1996, but it was more than 10 years before any of the zygomycete fungi, which are the early-diverging terrestrial fungi currently placed in the phyla Mucoromycota and Zoopagomycota, were sequenced. The genome for Rhizopus delemar was completed in 2008; currently, more than 1000 zygomycete genomes have been sequenced. Genomic data from these early-diverging terrestrial fungi revealed deep phylogenetic separation of the two major clades—primarily plant—associated saprotrophic and mycorrhizal Mucoromycota versus the primarily mycoparasitic or animal-associated parasites and commensals in the Zoopagomycota. Genomic studies provide many valuable insights into how these fungi evolved in response to the challenges of living on land, including adaptations to sensing light and gravity, development of hyphal growth, and co-existence with the first terrestrial plants. Genome sequence data have facilitated studies of genome architecture, including a history of genome duplications and horizontal gene transfer events, distribution and organization of mating type loci, rDNA genes and transposable elements, methylation processes, and genes useful for various industrial applications. Pathogenicity genes and specialized secondary metabolites have also been detected in soil saprobes and pathogenic fungi. Novel endosymbiotic bacteria and viruses have been discovered during several zygomycete genome projects. Overall, genomic information has helped to resolve a plethora of research questions, from the placement of zygomycetes on the evolutionary tree of life and in natural ecosystems, to the applied biotechnological and medical questions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Complete genome sequence of the rapeseed plant-growth promoting Serratia plymuthica strain AS9

Serratia plymuthica are plant-associated, plant beneficial species belonging to the family Enterobacteriaceae. The members of the genus Serratia are ubiquitous in nature and their life style varies from endophytic to free-living. S. plymuthica AS9 is of special interest for its ability to inhibit fungal pathogens of rapeseed and to promote plant growth. The genome of S. plymuthica AS9 comprises a 5,442,880 bp long circular chromosome that consists of 4,952 protein-coding genes, 87 tRNA genes and 7 rRNA operons. This genome is part of the project entitled Genomics of four rapeseed plant growth promoting bacteria with antagonistic effect on plant pathogens awarded through the 2010 DOE-JGI Community Sequencing Program (CSP2010).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Complete genome sequence of Serratia plymuthica strain AS12

A plant associated member of the family Enterobacteriaceae, Serratia plymuthica strain AS12 was isolated from rapeseed roots. It is of scientific interest due to its plant growth promoting and plant pathogen inhibiting ability. The genome of S. plymuthica AS12 comprises a 5,443,009 bp long circular chromosome, which consists of 4,952 protein-coding genes, 87 tRNA genes and 7 rRNA operons. This genome was sequenced within the 2010 DOE-JGI Community Sequencing Program (CSP2010) as part of the project entitled 'Genomics of four rapeseed plant growth promoting bacteria with antagonistic effect on plant pathogens'.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Prediction of bacterial E3 ubiquitin ligase effectors using reduced amino acid peptide fingerprinting

Background Although pathogenic Gram-negative bacteria lack their own ubiquitination machinery, they have evolved or acquired virulence effectors that can manipulate the host ubiquitination process through structural and/or functional mimicry of host machinery. Many such effectors have been identified in a wide variety of bacterial pathogens that share little sequence similarity amongst themselves or with eukaryotic ubiquitin E3 ligases. Methods To allow identification of novel bacterial E3 ubiquitin ligase effectors from protein sequences we have developed a machine learning approach, the SVM-based Identification and Evaluation of Virulence Effector Ubiquitin ligases (SIEVE-Ub). We extend the string kernel approach used previously to sequence classification by introducing reduced amino acid (RED) alphabet encoding for protein sequences. Results We found that 14mer peptides with amino acids represented as simply either hydrophobic or hydrophilic provided the best models for discrimination of E3 ligases from other effector proteins with a receiver-operator characteristic area under the curve (AUC) of 0.90. When considering a subset of E3 ubiquitin ligase effectors that do not fall into known sequence based families we found that the AUC was 0.82, demonstrating the effectiveness of our method at identifying novel functional family members. Feature selection was used to identify a parsimonious set of 10 RED peptides that provided good discrimination, and these peptides were found to be located in functionally important regions of the proteins involved in E2 and host target protein binding. Our general approach enables construction of models based on other effector functions. We used SIEVE-Ub to predict nine potential novel E3 ligases from a large set of bacterial genomes. SIEVE-Ub is available for download at https://doi.org/10.6084/m9.figshare.7766984.v1 or https://github.com/biodataganache/SIEVE-Ub for the most current version.

59 BASIC BIOLOGICAL SCIENCES↗