Development and evaluation of ActSeq: A targeted next-generation sequencing panel for clinical oncology use.

PURPOSE: The demand for high-throughput genetic profiling of somatic mutations in cancer tissues is growing. We sought to establish a targeted next generation sequencing (NGS) panel test for clinical oncology practice. METHODS: Customized probes were designed to capture exonic regions of 141 genes selected for the panel, which was aimed for the detection of clinically actionable genetic variations in cancer, including KRAS, NRAS, BRAF, ALK, ROS1, KIT and EGFR. The size of entire targeted regions is 0.8 Mb. Library preparation used NEBNext Ultra II FS kit coupled with target enrichment. Paired-end sequencing was run on Illumina NextSeq 500 at a read length of 150 nt. A bioinformatics workflow focusing on single nucleotide variant and short insertions and deletions (SNV/indel) discovery was established using open source, in-house and commercial software tools. Standard reference DNA samples were used in testing the sensitivity and precision and limit of detection in variant calling. RESULTS: The general performance of the panel was observed in pilot runs. Average total reads per sample ranged from 30 million to 48 million, 73% ~82% unique reads. All runs had more than 99% average mapping rate. Mean target coverage ranged from 727x to 879x. Depth of coverage at 50x or more reached 87% of targeted region and 60% of targeted region received 500x or more coverage depth. Using OncoSpan HD827 DNA, which bears 144 variants (SNV/indel) from 80 genes that are within the targeted region on the panel, our somatic variant calling pipeline reached 97% sensitivity and 100% precision respectively, with near 48 million reads. High concordance with orthogonal approaches in variant detection was further verified with 7 cancer cell lines and 45 clinical specimens. CONCLUSION: We developed a NGS panel with a focus on clinically actionable gene mutations and validated the performance in library construction, sequencing and variant calling. High concordance with reference materials and orthogonal mutation detection was observed.

A novel urine peptide biomarker-based algorithm for the prognosis of necrotising enterocolitis in human infants.

OBJECTIVE: Necrotising enterocolitis (NEC) is a major source of neonatal morbidity and mortality. The management of infants with NEC is currently complicated by our inability to accurately identify those at risk for progression of disease prior to the development of irreversible intestinal necrosis. We hypothesised that integrated analysis of clinical parameters in combination with urine peptide biomarkers would lead to improved prognostic accuracy in the NEC population. DESIGN: Infants under suspicion of having NEC (n=550) were prospectively enrolled from a consortium consisting of eight university-based paediatric teaching hospitals. Twenty-seven clinical parameters were used to construct a multivariate predictor of NEC progression. Liquid chromatography/mass spectrometry was used to profile the urine peptidomes from a subset of this population (n=65) to discover novel biomarkers of NEC progression. An ensemble model for the prediction of disease progression was then created using clinical and biomarker data. RESULTS: The use of clinical parameters alone resulted in a receiver-operator characteristic curve with an area under the curve of 0.817 and left 40.1% of all patients in an 'indeterminate' risk group. Three validated urine peptide biomarkers (fibrinogen peptides: FGA1826, FGA1883 and FGA2659) produced a receiver-operator characteristic area under the curve of 0.856. The integration of clinical parameters with urine biomarkers in an ensemble model resulted in the correct prediction of NEC outcomes in all cases tested. CONCLUSIONS: Ensemble modelling combining clinical parameters with biomarker analysis dramatically improves our ability to identify the population at risk for developing progressive NEC.

16S ribosomal RNA tools identify an unexpected predominance of Paenibacillus-like bacteria in an industrial activated sludge system suffering from poor biosolids separation.

Molecular biology tools targeting 16S ribosomal RNA (16S rRNA) were used to identify a predominant bacterial population in a full-scale dairy wastewater activated sludge system suffering from poor biosolids separation. Gram and acridine orange staining indicated that viable, Gram-positive microorganisms were present in samples removed from the influent waste stream and represented approximately 50% of total cell counts in samples removed from the mixed liquor. Subsequently, the "full-cycle 16S rRNA approach" showed that phylogenetic relatives of Paenibacillus spp., a low guanine-plus-cytosine percent DNA-content, Gram-positive microorganism, represented up to 30% of total 4,6-diamidino-2-phenylindole (DAPI)-stained cell counts in samples of mixed liquor. Although fluorescent in situ hybridizations with 16S rRNA-targeted oligonucleotide hybridization probes identified Paenibacillus-like spp. in samples removed from the influent waste stream, their abundance was less than 10% of total stained cell counts. Results of this study suggest that Paenibacillus-like spp. were present in low abundance in the influent waste stream, increased in relative abundance within the treatment system, and should be examined further as a candidate bacterial population responsible for poor biosolids separation. This study demonstrates that the full-cycle 16S rRNA approach can be used to identify candidate bacterial populations that may be responsible for operational upsets in full-scale activated sludge systems without prior information from cultivation or microscopic analyses.

Rapid PCR confirmation of E. coli O157:H7 after evanescent wave fiber optic biosensor detection.

Escherichia coli O157:H7 is an enteric pathogen of public health importance, which is monitored by several government agencies. Many rapid detection tests have been developed to identify foodstuff and water supplies contaminated by E. coli O157:H7. However, these methods can be time consuming (24-48 h) due to the need to culture the bacteria to confirm detection results. Fiber optic biosensors can rapidly detect pathogens from complex matrices, yet confirmation tests can take up to 10h to complete. In addition, fiber optic biosensors can also be used to reduce the impact of PCR inhibitors present in complex matrices such as food and water. This paper presents methodologies to reduce the time necessary for confirmation from 10 to about 2 h, by direct PCR of bacteria from the fiber optic waveguides without the need for culture or enrichment steps.

Current and developing technologies for monitoring agents of bioterrorism and biowarfare.

Recent events have made public health officials acutely aware of the importance of rapidly and accurately detecting acts of bioterrorism. Because bioterrorism is difficult to predict or prevent, reliable platforms to rapidly detect and identify biothreat agents are important to minimize the spread of these agents and to protect the public health. These platforms must not only be sensitive and specific, but must also be able to accurately detect a variety of pathogens, including modified or previously uncharacterized agents, directly from complex sample matrices. Various commercial tests utilizing biochemical, immunological, nucleic acid, and bioluminescence procedures are currently available to identify biological threat agents. Newer tests have also been developed to identify such agents using aptamers, biochips, evanescent wave biosensors, cantilevers, living cells, and other innovative technologies. This review describes these current and developing technologies and considers challenges to rapid, accurate detection of biothreat agents. Although there is no ideal platform, many of these technologies have proved invaluable for the detection and identification of biothreat agents.

Host distributions of uncultivated fecal Bacteroidales bacteria reveal genetic markers for fecal source identification.

The purpose of this study was to examine host distribution patterns among fecal bacteria in the order Bacteroidales, with the goal of using endemic sequences as markers for fecal source identification in aquatic environments. We analyzed Bacteroidales 16S rRNA gene sequences from the feces of eight hosts: human, bovine, pig, horse, dog, cat, gull, and elk. Recovered sequences did not match database sequences, indicating high levels of uncultivated diversity. The analysis revealed both endemic and cosmopolitan distributions among the eight hosts. Ruminant, pig, and horse sequences tended to form host- or host group-specific clusters in a phylogenetic tree, while human, dog, cat, and gull sequences clustered together almost exclusively. Many of the human, dog, cat, and gull sequences fell within a large branch containing cultivated species from the genus Bacteroides. Most of the cultivated Bacteroides species had very close matches with multiple hosts and thus may not be useful targets for fecal source identification. A large branch containing cultivated members of the genus Prevotella included cloned sequences that were not closely related to cultivated Prevotella species. Most ruminant sequences formed clusters separate from the branches containing Bacteroides and Prevotella species. Host-specific sequences were identified for pigs and horses and were used to design PCR primers to identify pig and horse sources of fecal pollution in water. The primers successfully amplified fecal DNAs from their target hosts and did not amplify fecal DNAs from other species. Fecal bacteria endemic to the host species may result from evolution in different types of digestive systems.

Risk factors for feline coronavirus seropositivity in cats relinquished to a UK rescue charity.

Two thousand, two hundred and seven cats from 14 shelters of a major UK cat charity were blood tested for feline coronavirus (FCoV) antibodies. Data was collated on breed, sex, age, number of cats at original location, outdoor access, health status, and time spent in the shelter prior to sampling (range 0 to 4 years). Some cats were also tested for feline leukaemia virus antigen, feline immunodeficiency virus, and Toxoplasma gondii antibodies. The effect of these variables on FCoV seropositivity was explored by multivariable logistic regression. FCoV seropositivity in cats that had spent 5 days or less in a shelter at sampling was significantly associated with a multi-cat origin, cats aged 3 years or less, and Persian breed. Whether pet, stray or feral, health status, indoor/outdoor access, and sex had no significant effect. Overall FCoV seropositivity was associated with time spent in a shelter but this association was not linear. Cats that had spent more than 60 days in a shelter were over five times as likely to be seropositive. This may be the result of a change in husbandry from solitary to communal housing for cats remaining in shelters long term. Rescue of cats for less than 60 days was not associated with a significant increasing risk of seropositivity. Significant variation existed in seropositivity between individual shelters overall and in cats rescued for less than 5 days. These findings may reflect inter-shelter variation in cat husbandry and variation in seropositivity of shelter intake respectively.

Assessment of equine fecal contamination: the search for alternative bacterial source-tracking targets.

16S rDNA clone libraries were evaluated for detection of fecal source-identifying bacteria from a collapsed equine manure pile. Libraries were constructed using universal eubacterial primers and Bacteroides-Prevotella group-specific primers. Eubacterial sequences indicated that upstream and downstream water samples were predominantly beta- and gamma-Proteobacteria (35 and 19%, respectively), while the manure library consisted predominantly of Firmicutes (31%) and previously unidentified sequences (60%). Manure-specific eubacterial sequences were not detectable beyond 5 m downstream of the pile, suggesting either poor survival or high dilution rates. In contrast, Bacteroides and Prevotella sp. sequences were detected both in manure and downstream using group-specific primers. Novel sequences from Bacteroides and Prevotella analysis produced an equine-specific phylogenetic cluster as compared to previous data sets obtained for human and bovine samples. While these results suggest that some anaerobic fecal bacteria might be potential identifiers for use in source-tracking applications, a comprehensive examination of environmental sequences within these species should be performed before methods targeting these bacterial groups are applied to watersheds for development of microbial source-tracking protocols.

Comparative microbial diversity in the gastrointestinal tracts of food animal species.

Molecular tools based on small subunit (SSU) rDNA gene sequences offer a powerful and rapid tool for the analysis of complex microbial communities found in the gastrointestinal tracts (GIT) of food animal species. Extensive comparative sequence analysis of SSU rRNA molecules representing a wide diversity of organisms shows that different regions of the molecule vary in sequence conservation. Oligonucleotides complementing regions of universally conversed SSU rRNA sequences are used as universal probes, while those complementing more variable regions of sequence are useful as selective probes targeting species, genus, or phylogenetic groups. Different approaches derive different information and this is highly dependent on the type of target nucleic acid employed and the conceptual and technical basis used for nucleic acid probe design. Generally these approaches can be divided into DNA-based methods employing empirically characterized probes and rRNA-based methods based on comparative sequence analysis for design and interpretation of "rational" probes. Polymerase chain reaction (PCR) based techniques can also be applied to the analysis of microbial communities in the GIT. Direct cloning of SSU rDNA genes amplified from these complex communities can be used to determine the extent of diversity in these GIT communities. Denaturing gradient gel electrophoresis (DGGE) is another powerful tool for profiling microbial diversity of microbial communities in GI tracts. Sequence analysis of the excised DGGE amplicons can then be used to presumptively identify predominant bacterial species. Examples of how these molecular approaches are being used to study the microbial diversity of communities from steers fed different diets, swine fed probiotics, and Atlantic salmon fed aquaculture diets are presented.

Microbial source tracking: state of the science.

Although water quality of the Nation's lakes, rivers and streams has been monitored for many decades and especially since the passage of the Clean Water Act in 1972, many still do not meet the Act's goal of "fishable and swimmable". While waterways can be impaired in numerous ways, the protection from pathogenic microbe contamination is most important for waters used for human recreation, drinking water and aquaculture. Typically, monitoring methods used for detecting potential pathogenic microorganisms in environmental waters are based upon cultivation and enumeration of fecal indicator bacteria (i.e. fecal coliforms, E. coli, and fecal enterococci). Currently, there is increasing interest in the potential for molecular fingerprinting methods to be used not only for detection but also for identification of fecal contamination sources. Molecular methods have been applied to study the microbial ecology of environmental systems for years and are now being applied to help improve our waters by identifying problem sources and determining the effect of implemented remedial solutions. Management and remediation of water pollution would be more cost-effective if the correct sources could be identified. This review provides an outline of the main methods that either have been used or have been suggested for use in microbial source tracking and some of the limitations associated with those methods.