Genomic Epidemiology of Campylobacter jejuni Transmission in Israel

Objectives:Campylobacter jejuni is responsible for 80% of Campylobacter infections in Israel, a country with a high incidence reaching 91/100,000 population. We studied the phylogeny, diversity and prevalence of virulence factors using whole genome sequencing (WGS) of a national sample of C. jejuni clinical, food, and animal isolates collected over a 10-year period (2003–2012).Methods:C. jejuni isolates (n = 263) were subject to WGS using Illumina sequencing (PE 250bpx2). Raw reads and de novo assemblies were analyzed with the BioNumerics whole genome MLST (wgMLST) pipeline. Reads were screened for 71 virulence genes by the SRST2 script. Allelic profiles were analyzed to create minimum spanning trees and allelic core distances were investigated to determine a reliable cutoff for strain determination.Results: wgMLST analysis of 263 C. jejuni isolates indicated significant diversity among the prevalent clonal complexes (CCs) with CC-21 and CC-353 being the most diverse, and CC-574 the most clonal. Within CC-21, sequence type (ST)-1359 created a separate clade. Human, poultry and bovine isolates clustered together across the different STs. Forty four percent of studied isolates were assigned to 29 genetic clusters. Temporal and geographical relatedness were found among the minority of clusters, while most phylogenetically associated cases appeared diffuse and unassociated epidemiologically. The majority of virulence factors were highly prevalent across the dataset and not associated with genotype, source of isolation or invasiveness. Conversely, all 13 genes associated with type VI secretion system (T6SS) were lineage-related and identified in only 18% of the isolates. T6SS was detected in 95.2% of ST-1359, a common type in Israel.Conclusions: wgMLST supported the assessment that poultry and cattle are likely food sources of infection in Israel. Substantial genetic clustering among C. jejuni isolates suggested multiple point source and diffuse outbreaks that were previously unreported in Israel. The high prevalence of T6SS among ST-1359 isolates is unique to Israel, and requires further investigation. This study exemplifies the importance of studying foodborne pathogens using advanced genomic approaches across the entire spectrum of One Health

Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption

Designing privacy-preserving deep learning models is a major challenge within the deep learning community. Homomorphic Encryption (HE) has emerged as one of the most promising approaches in this realm, enabling the decoupling of knowledge between the model owner and the data owner. Despite extensive research and application of this technology, primarily in convolutional neural networks, incorporating HE into transformer models has been challenging because of the difficulties in converting these models into a polynomial form. We break new ground by introducing the first polynomial transformer, providing the first demonstration of secure inference over HE with transformers. This includes a transformer architecture tailored for HE, alongside a novel method for converting operators to their polynomial equivalent. This innovation enables us to perform secure inference on LMs with WikiText-103. It also allows us to perform image classification with CIFAR-100 and Tiny-ImageNet. Our models yield results comparable to traditional methods, bridging the performance gap with transformers of similar scale and underscoring the viability of HE for state-of-the-art applications. Finally, we assess the stability of our models and conduct a series of ablations to quantify the contribution of each model component.Comment: 6 figure

Monkeypox: another test for PCR

Monkeypox was declared a public health emergency of international concern by the World Health Organization (WHO) on 23 July 2022. Between 1 January and 23 July 2022, 16,016 laboratory confirmed cases of monkeypox and five deaths were reported to WHO from 75 countries on all continents. Public health authorities are proactively identifying cases and tracing their contacts to contain its spread. As with COVID-19, PCR is the only method capable of being deployed at sufficient speed to provide timely feedback on any public health interventions. However, at this point, there is little information on how those PCR assays are being standardised between laboratories. A likely reason is that testing is still limited on a global scale and that detection, not quantification, of monkeypox virus DNA is the main clinical requirement. Yet we should not be complacent about PCR performance. As testing requirements increase rapidly and specimens become more diverse, it would be prudent to ensure PCR accuracy from the outset to support harmonisation and ease regulatory conformance. Lessons from COVID-19 should aid implementation with appropriate material, documentary and methodological standards offering dynamic mechanisms to ensure testing that most accurately guides public health decisions

HeLayers: A Tile Tensors Framework for Large Neural Networks on Encrypted Data

Privacy-preserving solutions enable companies to offload confidential data to third-party services while fulfilling their government regulations. To accomplish this, they leverage various cryptographic techniques such as Homomorphic Encryption (HE), which allows performing computation on encrypted data. Most HE schemes work in a SIMD fashion, and the data packing method can dramatically affect the running time and memory costs. Finding a packing method that leads to an optimal performant implementation is a hard task. We present a simple and intuitive framework that abstracts the packing decision for the user. We explain its underlying data structures and optimizer, and propose a novel algorithm for performing 2D convolution operations. We used this framework to implement an HE-friendly version of AlexNet, which runs in three minutes, several orders of magnitude faster than other state-of-the-art solutions that only use HE.Comment: 17 pages, 7 figure

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

chewBBACA : A complete suite for gene-by-gene schema creation and strain identification

Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.Peer reviewe

Proficiency testing for bacterial whole genome sequencing: an end-user survey of current capabilities, requirements and priorities

The advent of next-generation sequencing (NGS) has revolutionised public health microbiology. Given the potential impact of NGS, it is paramount to ensure standardisation of ‘wet’ laboratory and bioinformatic protocols and promote comparability of methods employed by different laboratories and their outputs. Therefore, one of the ambitious goals of the Global Microbial Identifier (GMI) initiative (http://www.globalmicrobialidentifier.org/) has been to establish a mechanism for inter-laboratory NGS proficiency testing (PT). This report presents findings from the survey recently conducted by Working Group 4 among GMI members in order to ascertain NGS end-use requirements and attitudes towards NGS PT. The survey identified the high professional diversity of laboratories engaged in NGS-based public health projects and the wide range of capabilities within institutions, at a notable range of costs. The priority pathogens reported by respondents reflected the key drivers for NGS use (high burden disease and ‘high profile’ pathogens). The performance of and participation in PT was perceived as important by most respondents. The wide range of sequencing and bioinformatics practices reported by end-users highlights the importance of standardisation and harmonisation of NGS in public health and underpins the use of PT as a means to assuring quality. The findings of this survey will guide the design of the GMI PT program in relation to the spectrum of pathogens included, testing frequency and volume as well as technical requirements. The PT program for external quality assurance will evolve and inform the introduction of NGS into clinical and public health microbiology practice in the post-genomic era. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-015-0902-3) contains supplementary material, which is available to authorized users

Expert Guidance on Target Product Profile Development for AMR Diagnostic Tests

Diagnostics are widely considered crucial in the fight against antimicrobial resistance (AMR), which is expected to kill 10 million people annually by 2030. Nevertheless, there remains a substantial gap between the need for AMR diagnostics versus their development and implementation. To help address this problem, target product profiles (TPP) have been developed to focus developers’ attention on the key aspects of AMR diagnostic tests. However, during discussion between a multisectoral working group of 51 international experts from industry, academia and healthcare, it was noted that specific AMR-related TPPs could be extended by incorporating the interdependencies between the key characteristics associated with the development of such TPPs. Subsequently, the working group identified 46 characteristics associated with six main categories (i.e., Intended Use, Diagnostic Question, Test Description, Assay Protocol, Performance and Commercial). The interdependencies of these characteristics were then identified and mapped against each other to generate new insights for use by stakeholders. Specifically, it may not be possible for diagnostics developers to achieve all of the recommendations in every category of a TPP and this publication indicates how prioritising specific TPP characteristics during diagnostics development may influence (or not) a range of other TPP characteristics associated with the diagnostic. The use of such guidance, in conjunction with specific TPPs, could lead to more efficient AMR diagnostics development