A Quantitative Assessment of Staphylococcus aureus Community Carriage in Yuma, Arizona.

BACKGROUND: Disease control relies on pathogen identification and understanding reservoirs. Staphylococcus aureus infection prevention is based upon decades of research on colonization and infection, but diminishing returns from mitigation efforts suggest significant knowledge gaps. Existing knowledge and mitigation protocols are founded upon culture-based detection, with almost no information about pathogen quantities. METHODS: We used culture and a quantitative polymerase chain reaction assay on samples from 3 body sites to characterize colonization more comprehensively than previous studies by describing both prevalence and pathogen quantity. RESULTS: We show a much higher overall prevalence (65.9%) than previously documented, with higher quantities and prevalence associated with the nares, non-Hispanic males (86.9%), and correlating with colonization in other body sites. These results suggest that research and clinical practices likely misclassify over half of colonized persons, limiting mitigation measures and their impact. CONCLUSIONS: This work begins the process of rebuilding foundational knowledge of S aureus carriage with more accurate and wholistic approaches.

Selective whole genome amplification and sequencing of Coxiella burnetii directly from environmental samples.

Whole genome sequencing (WGS) is a widely available, inexpensive means of providing a wealth of information about an organism's diversity and evolution. However, WGS for many pathogenic bacteria remain limited because they are difficult, slow and/or dangerous to culture. To avoid culturing, metagenomic sequencing can be performed directly on samples, but the sequencing effort required to characterize low frequency organisms can be expensive. Recently developed methods for selective whole genome amplification (SWGA) can enrich target DNA to provide efficient sequencing. We amplified Coxiella burnetii (a bacterial select agent and human/livestock pathogen) from 3 three environmental samples that were overwhelmed with host DNA. The 68- to 147-fold enrichment of the bacterial sequences provided enough genome coverage for SNP analyses and phylogenetic placement. SWGA is a valuable tool for the study of difficult-to-culture organisms and has the potential to facilitate high-throughput population characterizations as well as targeted epidemiological or forensic investigations.

Epidemiology of Incarceration: Characterizing Jail Incarceration for Public Health Research.

BACKGROUND: Each year, 9 million individuals cycle in and out of jails. The under-characterization of incarceration as an exposure poses substantial challenges to understanding how varying levels of exposure to jail may affect health. Thus, we characterized levels of jail incarceration including recidivism, number of incarcerations, total and average number of days incarcerated, and time to reincarceration. METHODS: We created a cohort of 75,203 individuals incarcerated at the Coconino County Detention Facility in Flagstaff, Arizona, from 2001 to 2018 from jail intake and release records. RESULTS: The median number of incarcerations during the study period was one (interquartile range [IQR] = 1-2). Forty percent of individuals had >1 incarceration. The median length of stay for first observed incarcerations was 1 day (IQR = 0-5). The median total days incarcerated was 3 (IQR = 1-23). Average length of stay increased by number of incarcerations. By 18 months, 27% of our sample had been reincarcerated. CONCLUSION: Characteristics of jail incarceration have been largely left out of public health research. A better understanding of jail incarcerations can help design analyses to assess health outcomes of individuals incarcerated in jail. Our study is an early step in shaping an understanding of jail incarceration as an exposure for future epidemiologic research. See video abstract at, http://links.lww.com/EDE/B536.

Variant site strain typer (VaST): efficient strain typing using a minimal number of variant genomic sites.

BACKGROUND: Targeted PCR amplicon sequencing (TAS) techniques provide a sensitive, scalable, and cost-effective way to query and identify closely related bacterial species and strains. Typically, this is accomplished by targeting housekeeping genes that provide resolution down to the family, genera, and sometimes species level. Unfortunately, this level of resolution is not sufficient in many applications where strain-level identification of bacteria is required (biodefense, forensics, clinical diagnostics, and outbreak investigations). Adding more genomic targets will increase the resolution, but the challenge is identifying the appropriate targets. VaST was developed to address this challenge by finding the minimum number of targets that, in combination, achieve maximum strain-level resolution for any strain complex. The final combination of target regions identified by the algorithm produce a unique haplotype for each strain which can be used as a fingerprint for identifying unknown samples in a TAS assay. VaST ensures that the targets have conserved primer regions so that the targets can be amplified in all of the known strains and it also favors the inclusion of targets with basal variants which makes the set more robust when identifying previously unseen strains. RESULTS: We analyzed VaST's performance using a number of different pathogenic species that are relevant to human disease outbreaks and biodefense. The number of targets required to achieve full resolution ranged from 20 to 88% fewer sites than what would be required in the worst case and most of the resolution is achieved within the first 20 targets. We computationally and experimentally validated one of the VaST panels and found that the targets led to accurate phylogenetic placement of strains, even when the strains were not a part of the original panel design. CONCLUSIONS: VaST is an open source software that, when provided a set of variant sites, can find the minimum number of sites that will provide maximum resolution of a strain complex, and it has many different run-time options that can accommodate a wide range of applications. VaST can be an effective tool in the design of strain identification panels that, when combined with TAS technologies, offer an efficient and inexpensive strain typing protocol.

Genomic epidemiology of multidrug-resistant Mycobacterium tuberculosis during transcontinental spread.

The transcontinental spread of multidrug-resistant (MDR) tuberculosis is poorly characterized in molecular epidemiologic studies. We used genomic sequencing to understand the establishment and dispersion of MDR Mycobacterium tuberculosis within a group of immigrants to the United States. We used a genomic epidemiology approach to study a genotypically matched (by spoligotype, IS6110 restriction fragment length polymorphism, and mycobacterial interspersed repetitive units-variable number of tandem repeat signature) lineage 2/Beijing MDR strain implicated in an outbreak of tuberculosis among refugees in Thailand and consecutive cases within California. All 46 MDR M. tuberculosis genomes from both Thailand and California were highly related, with a median difference of 10 single-nucleotide polymorphisms (SNPs). The Wat Tham Krabok (WTK) strain is a new sequence type distinguished from all known Beijing strains by 55 SNPs and a genomic deletion (Rv1267c) associated with increased fitness. Sequence data revealed a highly prevalent MDR strain that included several closely related but distinct allelic variants within Thailand, rather than the occurrence of a single outbreak. In California, sequencing data supported multiple independent introductions of WTK with subsequent transmission and reactivation within the state, as well as a potential super spreader with a prolonged infectious period. Twenty-seven drug resistance-conferring mutations and 4 putative compensatory mutations were found within WTK strains. Genomic sequencing has substantial epidemiologic value in both low- and high-burden settings in understanding transmission chains of highly prevalent MDR strains.

Metagenomic analysis of the airborne environment in urban spaces.

The organisms in aerosol microenvironments, especially densely populated urban areas, are relevant to maintenance of public health and detection of potential epidemic or biothreat agents. To examine aerosolized microorganisms in this environment, we performed sequencing on the material from an urban aerosol surveillance program. Whole metagenome sequencing was applied to DNA extracted from air filters obtained during periods from each of the four seasons. The composition of bacteria, plants, fungi, invertebrates, and viruses demonstrated distinct temporal shifts. Bacillus thuringiensis serovar kurstaki was detected in samples known to be exposed to aerosolized spores, illustrating the potential utility of this approach for identification of intentionally introduced microbial agents. Together, these data demonstrate the temporally dependent metagenomic complexity of urban aerosols and the potential of genomic analytical techniques for biosurveillance and monitoring of threats to public health.

Population sequencing for diversity and transmission analyses.

Genomic diversity in a pathogen population is the foundation for evolution and adaptations in virulence, drug resistance, pathogenesis, and immune evasion. Characterizing, analyzing, and understanding population-level diversity is also essential for epidemiological and forensic tracking of sources and revealing detailed pathways of transmission and spread. For bacteria, culturing, isolating, and sequencing the large number of individual colonies required to adequately sample diversity can be prohibitively time-consuming and expensive. While sequencing directly from a mixed population will show variants among reads, they cannot be linked to reveal allele combinations associated with particular traits or phylogenetic inheritance patterns. Here, we describe the theory and method of how population sequencing directly from a mixed sample can be used in conjunction with sequencing a very small number of colonies to describe the phylogenetic diversity of a population without haplotype reconstruction. To demonstrate the utility of population sequencing in capturing phylogenetic diversity, we compared isogenic clones to population sequences of Burkholderia pseudomallei from the sputum of a single patient. We also analyzed population sequences of Staphylococcus aureus derived from different people and different body sites. Sequencing results confirm our ability to capture and characterize phylogenetic diversity in our samples. Our analyses of B. pseudomallei populations led to the surprising discovery that the pathogen population is highly structured in sputum, suggesting that for some pathogens, sputum sampling may preserve structuring in the lungs and thus present a non-invasive alternative to understanding colonization, movement, and pathogen/host interactions. Our analyses of S. aureus samples show how comparing phylogenetic diversity across populations can reveal directionality of transmission between hosts and across body sites, demonstrating the power and utility for characterizing the spread of disease and identification of reservoirs at the finest levels. We anticipate that population sequencing and analysis can be broadly applied to accelerate research in a broad range of fields reliant on a foundational understanding of population diversity. Author Summary: The ability to characterize diversity in a single bacterial population (i.e., a single host or even a single body site) is critical for understanding adaptation and evolution, with far-reaching implications on disease treatment and prevention that include revealing patterns of spread and persistence. While the scientific community has made great strides in sequencing methods to characterize single colonies and entire communities, there is a dearth of studies at the population level. This is because 1) the need to culture and sequence a sufficiently representative number of isogenic colonies is prohibitive, and 2) the theoretical foundation for characterizing a population by sequencing a single sample (as is done for microbiome and metagenomic analyses) has not been developed. Here, we introduce this theoretical foundation and validate its applicability by characterizing a lung infection caused by Burkholderia pseudomallei . We also demonstrate the utility of this method in determining the directionality of spread of Staphylococcus aureus between people and across body sites within the same host (a level of spatial resolution that has not been previously performed). We anticipate that this work will open the door to a host of new studies and discoveries across a diverse set of microbiological fields.

ColiSeq: a multiplex amplicon assay that provides strain level resolution of Escherichia coli directly from clinical specimens.

Escherichia coli is a diverse pathogen, causing a range of disease in humans, from self-limiting diarrhea to urinary tract infections (UTIs). Uropathogenic E. coli (UPEC) is the most frequently observed uropathogen in UTIs, a common disease in high-income countries, incurring billions of dollars yearly in treatment costs. Although E. coli is easily grown and identified in the clinical laboratory, genotyping the pathogen is more complicated, yet critical for reducing the incidence of disease. These goals can be achieved through whole-genome sequencing of E. coli isolates, but this approach is relatively slow and typically requires culturing the pathogen in the laboratory. To genotype E. coli rapidly and inexpensively directly from clinical samples, including but not limited to urine, we developed and validated a multiplex amplicon sequencing assay, called ColiSeq. The assay consists of targets designed for E. coli species confirmation, high resolution genotyping, and mixture deconvolution. To demonstrate its utility, we screened the ColiSeq assay against 230 clinical urine samples collected from a hospital system in Flagstaff, Arizona, USA. A limit of detection analysis demonstrated the ability of ColiSeq to identify E. coli at a concentration of ~2 genomic equivalent (GEs)/mL and to generate high-resolution genotyping at a concentration of 1 × 105 GEs/mL. The results of this study suggest that ColiSeq could be a valuable method to understand the source of UPEC strains and guide infection mitigation efforts. As sequence-based diagnostics become accepted in the clinical laboratory, workflows such as ColiSeq will provide actionable information to improve patient outcomes.IMPORTANCEUrinary tract infections (UTIs), caused primarily by Escherichia coli, create an enormous health care burden in the United States and other high-income countries. The early detection of E. coli from clinical samples, including urine, is important to target therapy and prevent further patient complications. Additionally, understanding the source of E. coli exposure will help with future mitigation efforts. In this study, we developed, tested, and validated an amplicon sequencing assay focused on direct detection of E. coli from urine. The resulting sequence data were demonstrated to provide strain level resolution of the pathogen, not only confirming the presence of E. coli, which can focus treatment efforts, but also providing data needed for source attribution and contact tracing. This assay will generate inexpensive, rapid, and reproducible data that can be deployed by public health agencies to track, diagnose, and potentially mitigate future UTIs caused by E. coli.

Host population structure and rare dispersal events drive leptospirosis transmission patterns among Rattus norvegicus in Boston, Massachusetts, US.

Leptospirosis (caused by pathogenic bacteria in the genus Leptospira ) is prevalent worldwide but more common in tropical and subtropical regions. Transmission can occur following direct exposure to infected urine from reservoir hosts, such as rats, or a urine-contaminated environment, which then can serve as an infection source for additional rats and other mammals, including humans. The brown rat, Rattus norvegicus , is an important reservoir of leptospirosis in urban settings. We investigated leptospirosis among brown rats in Boston, Massachusetts and hypothesized that rat dispersal in this urban setting influences the movement, persistence, and diversity of Leptospira . We analyzed DNA from 328 rat kidney samples collected from 17 sites in Boston over a seven-year period (2016-2022); 59 rats representing 12 of 17 sites were positive for Leptospira . We used 21 neutral microsatellite loci to genotype 311 rats and utilized the resulting data to investigate genetic connectivity among sampling sites. We generated whole genome sequences for 28 Leptospira isolates obtained from frozen and fresh tissue from some of the 59 Leptospira -positive rat kidneys. When isolates were not obtained, we attempted Leptospira genomic DNA capture and enrichment, which yielded 14 additional Leptospira genomes from rats. We also generated an enriched Leptospira genome from a 2018 human case in Boston. We found evidence of high genetic structure and limited dispersal among rat populations that is likely influenced by major roads and/or other unknown dispersal barriers, resulting in distinct rat population groups within the city; at certain sites these groups persisted for multiple years. We identified multiple distinct phylogenetic clades of L. interrogans among rats, with specific clades tightly linked to distinct rat populations. This pattern suggests L. interrogans persists in local rat populations and movement of leptospirosis in this urban rat community is driven by rat dispersal. Finally, our genomic analyses of the 2018 human leptospirosis case in Boston suggests a link to rats as the source. These findings will be useful for guiding rat control and human leptospirosis mitigation efforts in this and other urban settings.

Pan-Enterovirus Characterization Reveals Cryptic Circulation of Clinically Relevant Subtypes in Arizona Wastewater.

Background: Most seasonally circulating enteroviruses result in asymptomatic or mildly symptomatic infections. In rare cases, however, infection with some subtypes can result in paralysis or death. Of the 300 subtypes known, only poliovirus is reportable, limiting our understanding of the distribution of other enteroviruses that can cause clinical disease. Objective: The overarching objectives of this study were to: 1) describe the distribution of enteroviruses in Arizona during the late summer and fall of 2022, the time of year when they are thought to be most abundant, and 2) demonstrate the utility of viral pan-assay approaches for semi-agnostic discovery that can be followed up by more targeted assays and phylogenomics. Methods: This study utilizes pooled nasal samples collected from school-aged children and long-term care facility residents, and wastewater from multiple locations in Arizona during July-October of 2022. We used PCR to amplify and sequence a region common to all enteroviruses, followed by species-level bioinformatic characterization using the QIIME 2 platform. For Enterovirus-D68 (EV-D68), detection was carried out using RT-qPCR, followed by confirmation using near-complete whole EV-D68 genome sequencing using a newly designed tiled amplicon approach. Results: In the late summer and early fall of 2022, multiple enterovirus species were identified in Arizona wastewater, with Coxsackievirus A6, EV-D68, and Coxsackievirus A19 composing 86% of the characterized reads sequenced. While EV-D68 was not identified in pooled human nasal samples, and the only reported acute flaccid myelitis case in Arizona did not test positive for the virus, an in-depth analysis of EV-D68 in wastewater revealed that the virus was circulating from August through mid-October. A phylogenetic analysis on this relatively limited dataset revealed just a few importations into the state, with a single clade indicating local circulation. Significance: This study further supports the utility of wastewater-based epidemiology to identify potential public health threats. Our further investigations into EV-D68 shows how these data might help inform healthcare diagnoses for children presenting with concerning neurological symptoms.

Multi-faceted metagenomic analysis of spacecraft associated surfaces reveal planetary protection relevant microbial composition.

The National Aeronautics and Space Administration (NASA) has been monitoring the microbial burden of spacecraft since the 1970's Viking missions. Originally culture-based and then focused 16S sequencing techniques were used, but we have now applied whole metagenomic sequencing to a variety of cleanroom samples at the Jet Propulsion Lab (JPL), including the Spacecraft Assembly Facility (SAF) with the goals of taxonomic identification and for functional assignment. Our samples included facility pre-filters, cleanroom vacuum debris, and surface wipes. The taxonomic composition was carried out by three different analysis tools to contrast marker, k-mer, and true alignment approaches. Hierarchical clustering analysis of the data separated vacuum particles from other SAF DNA samples. Vacuum particle samples were the most diverse while DNA samples from the ISO (International Standards Organization) compliant facilities and the SAF were the least diverse; all three were dominated by Proteobacteria. Wipe samples had higher diversity and were predominated by Actinobacteria, including human commensals Cutibacterium acnes and Corynebacterium spp. Taxa identified by the three methods were not identical, supporting the use of multiple methods for metagenome characterization. Likewise, functional annotation was performed using multiple methods. Vacuum particles and SAF samples contained strong signals of the tricarboxylic acid cycle and of amino acid biosynthesis, suggesting that many of the identified microorganisms have the ability to grow in nutrient-limited environments. In total, 18 samples generated high quality metagenome assembled genomes (MAG), which were dominated by Moraxella osloensis or Malassezia restricta. One M. osloensis MAG was assembled into a single circular scaffold and gene annotated. This study includes a rigorous quantitative determination of microbial loads and a qualitative dissection of microbial composition. Assembly of multiple specimens led to greater confidence for the identification of particular species and their predicted functional roles.

MTSv: rapid alignment-based taxonomic classification and high-confidence metagenomic analysis.

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.

Rapid Response of Nitrogen Cycling Gene Transcription to Labile Carbon Amendments in a Soil Microbial Community.

Episodic inputs of labile carbon (C) to soil can rapidly stimulate nitrogen (N) immobilization by soil microorganisms. However, the transcriptional patterns that underlie this process remain unclear. In order to better understand the regulation of N cycling in soil microbial communities, we conducted a 48-h laboratory incubation with agricultural soil where we stimulated the uptake of inorganic N by amending the soil with glucose. We analyzed the metagenome and metatranscriptome of the microbial communities at four time points that corresponded with changes in N availability. The relative abundances of genes remained largely unchanged throughout the incubation. In contrast, glucose addition rapidly increased the transcription of genes encoding ammonium and nitrate transporters, enzymes responsible for N assimilation into biomass, and genes associated with the N regulatory network. This upregulation coincided with an increase in transcripts associated with glucose breakdown and oxoglutarate production, demonstrating a connection between C and N metabolism. When concentrations of ammonium were low, we observed a transient upregulation of genes associated with the nitrogen-fixing enzyme nitrogenase. Transcripts for nitrification and denitrification were downregulated throughout the incubation, suggesting that dissimilatory transformations of N may be suppressed in response to labile C inputs in these soils. These results demonstrate that soil microbial communities can respond rapidly to changes in C availability by drastically altering the transcription of N cycling genes.IMPORTANCE A large portion of activity in soil microbial communities occurs in short time frames in response to an increase in C availability, affecting the biogeochemical cycling of nitrogen. These changes are of particular importance as nitrogen represents both a limiting nutrient for terrestrial plants as well as a potential pollutant. However, we lack a full understanding of the short-term effects of labile carbon inputs on the metabolism of microbes living in soil. Here, we found that soil microbial communities responded to labile carbon addition by rapidly transcribing genes encoding proteins and enzymes responsible for inorganic nitrogen acquisition, including nitrogen fixation. This work demonstrates that soil microbial communities respond within hours to carbon inputs through altered gene expression. These insights are essential for an improved understanding of the microbial processes governing soil organic matter production, decomposition, and nutrient cycling in natural and agricultural ecosystems.

St. Louis Encephalitis Virus in the Southwestern United States: A Phylogeographic Case for a Multi-Variant Introduction Event.

Since the reemergence of St. Louis Encephalitis (SLE) Virus (SLEV) in the Southwest United States, identified during the 2015 outbreak in Arizona, SLEV has been seasonally detected within Culex spp. populations throughout the Southwest United States. Previous work revealed the 2015 outbreak was caused by an importation of SLEV genotype III, which had only been detected previously in Argentina. However, little is known about when the importation occurred or the transmission and genetic dynamics since its arrival into the Southwest. In this study, we sought to determine whether the annual detection of SLEV in the Southwest is due to enzootic cycling or new importations. To address this question, we analyzed 174 SLEV genomes (142 sequenced as part of this study) using Bayesian phylogenetic analyses to estimate the date of arrival into the American Southwest and characterize the underlying population structure of SLEV. Phylogenetic clustering showed that SLEV variants circulating in Maricopa and Riverside counties form two distinct populations with little evidence of inter-county transmission since the onset of the outbreak. Alternatively, it appears that in 2019, Yuma and Clark counties experienced annual importations of SLEV that originated in Riverside and Maricopa counties. Finally, the earliest representatives of SLEV genotype III in the Southwest form a polytomy that includes both California and Arizona samples. We propose that the initial outbreak most likely resulted from the importation of a population of SLEV genotype III variants, perhaps in multiple birds, possibly multiple species, migrating north in 2013, rather than a single variant introduced by one bird.

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction.

BACKGROUND: Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels. RESULTS: This paper describes two key results that can be used separately or in combination for protein function analysis. The Family-wise Analysis of SubStructural Templates (FASST) method uses all-against-all substructure comparison to determine Substructural Clusters (SCs). SCs characterize the binding site substructural variation within a protein family. In this paper we focus on examples of automatically determined SCs that can be linked to phylogenetic distance between family members, segregation by conformation, and organization by homology among convergent protein lineages. The Motif Ensemble Statistical Hypothesis (MESH) framework constructs a representative motif for each protein cluster among the SCs determined by FASST to build motif ensembles that are shown through a series of function prediction experiments to improve the function prediction power of existing motifs. CONCLUSIONS: FASST contributes a critical feedback and assessment step to existing binding site substructure identification methods and can be used for the thorough investigation of structure-function relationships. The application of MESH allows for an automated, statistically rigorous procedure for incorporating structural variation data into protein function prediction pipelines. Our work provides an unbiased, automated assessment of the structural variability of identified binding site substructures among protein structure families and a technique for exploring the relation of substructural variation to protein function. As available proteomic data continues to expand, the techniques proposed will be indispensable for the large-scale analysis and interpretation of structural data.

Overexpression and mislocalization of the chromosomal segregation protein separase in multiple human cancers.

PURPOSE: Separase, an endopeptidase, plays a pivotal role in chromosomal segregation by separating sister chromatids during the metaphase to anaphase transition. Using a mouse mammary tumor model we have recently shown that overexpression of Separase induces aneuploidy and tumorigenesis (Zhang et al., Proc Natl Acad Sci 2008;105:13033). In the present study, we have investigated the expression level of Separase across a wide range of human tumors. EXPERIMENTAL DESIGN: To examine the expression levels and localization of Separase in human tumors, we have performed immunofluorescence microscopy using human Separase antibody and tumor tissue arrays from osteosarcoma, colorectal, breast, and prostate cancers with appropriate normal controls. RESULTS: We show that Separase is significantly overexpressed in osteosarcoma, breast, and prostate tumor specimens. There is a strong correlation of tumor status with the localization of Separase into the nucleus throughout all stages of the cell cycle. Unlike the normal control tissues, where Separase localization is exclusively cytoplasmic in nondividing cells, human tumor samples show significantly higher number of resting cells with a strong nuclear Separase staining. Additionally, overexpression of Separase transcript strongly correlates with high incidence of relapse, metastasis, and lower 5-year overall survival rate in breast and prostate cancer patients. CONCLUSION: These results further strengthen our hypothesis that Separase might be an oncogene, whose overexpression induces tumorigenesis, and indicates that Separase overexpression and aberrant nuclear localization are common in many tumor types and may predict outcome in some human cancers.

Sample pooling methods for efficient pathogen screening: Practical implications.

Due to the large number of negative tests, individually screening large populations for rare pathogens can be wasteful and expensive. Sample pooling methods improve the efficiency of large-scale pathogen screening campaigns by reducing the number of tests and reagents required to accurately categorize positive and negative individuals. Such methods rely on group testing theory which mainly focuses on minimizing the total number of tests; however, many other practical concerns and tradeoffs must be considered when choosing an appropriate method for a given set of circumstances. Here we use computational simulations to determine how several theoretical approaches compare in terms of (a) the number of tests, to minimize costs and save reagents, (b) the number of sequential steps, to reduce the time it takes to complete the assay, (c) the number of samples per pool, to avoid the limits of detection, (d) simplicity, to reduce the risk of human error, and (e) robustness, to poor estimates of the number of positive samples. We found that established methods often perform very well in one area but very poorly in others. Therefore, we introduce and validate a new method which performs fairly well across each of the above criteria making it a good general use approach.

Metagenomes and Metatranscriptomes of a Glucose-Amended Agricultural Soil.

The addition of glucose to soil has long been used to study the metabolic activity of microbes in soil; however, the response of the microbial ecophysiology remains poorly characterized. To address this, we sequenced the metagenomes and metatranscriptomes of glucose-amended soil microbial communities in a laboratory incubation.

A fecal sequel: Testing the limits of a genetic assay for bat species identification.

DNA metabarcoding assays are powerful tools for delving into the DNA in wildlife feces, giving unprecedented ability to detect species, understand natural history, and identify pathogens for a range of applications in management, conservation, and research. Next-generation sequencing technology is developing rapidly, which makes it especially important that predictability and reproducibility of DNA metabarcoding assays are explored together with the post-depositional ecology of the target taxon's fecal DNA. Here, we defined the constraints of an assay called 'Species from Feces' used by government agencies, research groups, and non-governmental organizations to identify bat species from guano. We tested assay sensitivity by examining how time and humidity affect the ability to recover and successfully sequence DNA in guano, assessing whether a fecal pellet from a rare bat species could be detected in a background of feces from other bat species, and evaluating the efficacy of Species from Feces as a survey tool for bat roosts in temperate and tropical areas. We found that the assay performs well with feces over two years old in dry, cool environments, and fails by 12 months at 100% relative humidity. We also found that it reliably identifies rare DNA, has great utility for surveying roosts in temperate and tropical regions, and detects more bat species than do visual surveys. We attribute the success of Species from Feces to characteristics of the assay paired with application in taxa that are particularly well-suited for fecal DNA survival. In a time of rapid evolution of DNA metabarcoding approaches and their use with feces, this study illustrates the strengths and limitations of applied assays.

Rapid Next-Generation Sequencing Method for Prediction of Prostate Cancer Risks.

Prostate cancer is the most commonly diagnosed male cancer and the second leading cause of cancer deaths among men in the United States, with approximately 220,000 new diagnoses and approximately 27,000 deaths each year. Men with clinical low-risk disease can receive active surveillance to safely preserve quality of life, provided that the risk of an undetected aggressive cancer can be managed. Thus, prediction of a tumor's metastatic potential, ideally using only a biopsy sample, is critical to choosing appropriate treatment. We previously proposed and verified a metastasis potential score (MPS) based on regions prone to copy number alterations in metastatic prostate cancer; MPS is highly predictive of metastatic potential in primary tumors. We developed a novel, targeted postligation amplification sequencing approach, which we call the next-generation copy number alteration assay, to efficiently interrogate 902 genomic sites that belong to 194 genomic regions used in the MPS calculation. The assay is designed to work with the latest generation of sequencing platforms to produce estimates of copy number alteration events. The assay's technical reproducibility, robustness to low starting genomic material, and accuracy have been verified. The assay performed very well on cell lines, a cohort of prostate cancer surgical research samples, and matched punched biopsy samples, making it a significant step toward incorporating sequencing techniques for prostate cancer evaluation.