Improving the time and space complexity of the WFA algorithm and generalizing its scoring

Modern genomic sequencing data is trending toward longer sequences with higher accuracy. Many analyses using these data will center on alignments, but classical exact alignment algorithms are infeasible for long sequences. The recently proposed WFA algorithm demonstrated how to perform exact alignment for long, similar sequences in O(sN) time and O(s2) memory, where s is a score that is low for similar sequences (Marco-Sola et al., 2021). However, this algorithm still has infeasible memory requirements for longer sequences. Also, it uses an alternate scoring system that is unfamiliar to many bioinformaticians. We describe variants of WFA that improve its asymptotic memory use from O(s2) to O(s3/2) and its asymptotic run time from O(sN) to O(s2 + N). We expect the reduction in memory use to be particularly impactful, as it makes it practical to perform highly multithreaded megabase-scale exact alignments in common compute environments. In addition, we show how to fold WFA's alternate scoring into the broader literature on alignment scores.

Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study

Background Incidental and screening-identified lung nodules are common, and a bronchoscopic evaluation is frequently nondiagnostic. The Percepta Genomic Sequencing Classifier (GSC) is a genomic classifier developed in current and former smokers which can be used for further risk stratification in these patients. Percepta GSC has the capability of up-classifying patients with a pre-bronchoscopy risk that is high (> 60%) to “very high risk” with a positive predictive value of 91.5%. This prospective, randomized decision impact survey was designed to test the hypothesis that an up-classification of risk of malignancy from high to very high will increase the rate of referral for surgical or ablative therapy without additional intervening procedures while increasing physician confidence. Methods Data were collected from 37 cases from the Percepta GSC validation cohort in which the pre-bronchoscopy risk of malignancy was high (> 60%), the bronchoscopy was nondiagnostic, and the patient was up-classified to very high risk by Percepta GSC. The cases were randomly presented to U.S pulmonologists in three formats: a pre-post cohort where each case is presented initially without and then with a GSG result, and two independent cohorts where each case is presented either with or without with a GSC result. Physicians were surveyed with respect to subsequent management steps and confidence in that decision. Results One hundred and one survey takers provided a total of 1341 evaluations of the 37 patient cases across the three different cohorts. The rate of recommendation for surgical resection was significantly higher in the independent cohort with a GSC result compared to the independent cohort without a GSC result (45% vs. 17%, p < 0.001) In the pre-post cross-over cohort, the rate increased from 17 to 56% (p < 0.001) following the review of the GSC result. A GSC up-classification from high to very high risk of malignancy increased Pulmonologists’ confidence in decision-making following a nondiagnostic bronchoscopy. Conclusions Use of the Percepta GSC classifier will allow more patients with early lung cancer to proceed more rapidly to potentially curative therapy while decreasing unnecessary intervening diagnostic procedures following a nondiagnostic bronchoscopy.

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

Collaboration between clinical and academic laboratories for sequencing SARS-CoV-2 genomes

Genomic sequencing of SARS-CoV-2 continues to provide valuable insight into the ever-changing variant makeup of the COVID-19 pandemic. More than three million SARS-COV-2 genomes have been deposited in GISAID, but contributions from the United States, particularly through 2020, lagged behind the global effort. The primary goal of clinical microbiology laboratories is seldom rooted in epidemiologic or public health testing and many labs do not contain in-house sequencing technology. However, we recognized the need for clinical microbiologists to lend expertise, share specimen resources, and partner with academic laboratories and sequencing cores to assist in SARS-COV-2 epidemiologic sequencing efforts. Here we describe two clinical and academic laboratory collaborations for SARS-COV-2 genomic sequencing. We highlight roles of the clinical microbiologists and the academic labs, outline best practices, describe two divergent strategies in accomplishing a similar goal, and discuss the challenges with implementing and maintaining such programs.

APTC-EC-2A: A Lytic Phage Targeting Multidrug Resistant E. coli Planktonic Cells and Biofilms

Escherichia coli (E. coli) are common bacteria that colonize the human and animal gastrointestinal tract, where they help maintain a balanced microbiome. However, some E. coli strains are pathogenic and can cause serious infectious diseases and life-threatening complications. Due to the overuse of antibiotics and limited development of novel antibiotics, the emergence of antibiotic-resistant strains has threatened modern medicine, whereby common infections can become lethal. Phage therapy has once again attracted interest in recent years as an alternative treatment option to antibiotics for severe infections with antibiotic-resistant strains. The aim of this study was to isolate and characterize phage against multi-drug resistant E. coli isolated from clinical samples and hospital wastewater. For phage isolation, wastewater samples were collected from The Queen Elizabeth Hospital (Adelaide, SA, Australia) followed by phage enrichment as required. Microbiological assays, electron microscopy and genomic sequencing were carried out to characterize the phage. From the 10 isolated E. coli phages, E. coli phage APTC-EC-2A was the most promising and could lyse 6/7 E. coli clinical isolates. APTC-EC-2A was stable at a broad pH range (3–11) and could lyse the host E. coli at temperatures ranging between 30–50 °C. Furthermore, APTC-EC-2A could kill E. coli in planktonic and biofilm form. Electron microscopy and genomic sequencing indicated the phage to be from the Myoviridae family and of lytic nature. In conclusion, the newly isolated phage APTC-EC-2A has the desired properties that support its potential for development as a therapeutic agent against therapy refractory E. coli infections.

Performance of COVIDSeq and Swift normalase amplicon SARS-CoV-2 panels for SARS-CoV-2 Genomes Sequencing: Practical Guide and Combining FASTQ Strategy

The whole genomic sequencing (WGS) of SARS-CoV-2 has been performed extensively and is playing a crucial role in fighting against COVID-19 pandemic. Obtaining sufficient WGS data from clinical samples is often challenging especially from the samples with low viral load. We evaluated two SARS-CoV-2 sequencing protocols for their efficiency/accuracy and limitations. Sequence coverage of >95% was obtained by Swift normalase amplicon SARS-CoV-2 panels (SNAP) protocol for all the samples with Ct ≤ 35 and by COVIDSeq protocol for 97% of samples with Ct ≤ 30. Sample RNA quantitation obtained using digital PCR provided more precise cutoff values. The quantitative digital PCR cutoff values for obtaining 95% coverage are 10.5 copies/μL for SNAP protocol and 147 copies/μL for COVIDSeq protocol. Combining FASTQ files obtained from 2 protocols improved the outcome of sequence analysis by compensating for missing amplicon regions. This process resulted in an increase of sequencing coverage and lineage call precision.