Insights from global data for use of rotavirus vaccines in India

Rotavirus vaccines are being introduced in several low- and middle-income countries across the world with and without support from the GAVI Alliance. India has the highest disease burden of rotavirus based on morbidity and mortality estimates and several indigenous vaccine manufacturers are developing rotavirus vaccines. One candidate has undergone phase III testing and others have completed evaluation in phase II. Global data on licensed vaccine performance in terms of impact on disease, strain diversity, safety and cost-effectiveness has been reviewed to provide a framework for decision making in India

Global diversity and antimicrobial resistance of typhoid fever pathogens : insights from a meta-analysis of 13,000 Salmonella Typhi genomes

DATA AVAILABILITY : All data analysed during this study are publicly accessible. Raw Illumina sequence reads have been submitted to the European Nucleotide Archive (ENA), and individual sequence accession numbers are listed in Supplementary file 2. The full set of n=13,000 genome assemblies generated for this study are available for download from FigShare: https://doi.org/10.26180/21431883. All assemblies of suitable quality (n=12,849) are included as public data in the online platform Pathogenwatch (https://pathogen.watch). The data are organised into collections, which each comprise a neighbour-joining phylogeny annotated with metadata, genotype, AMR determinants, and a linked map. Each contributing study has its own collection, browsable at https://pathogen.watch/collections/all?organismId= 90370. In addition, we have provided three large collections, each representing roughly a third of the total dataset presented in this study: Typhi 4.3.1.1 (https://pathogen.watch/collection/ 2b7mp173dd57-clade-4311), Typhi lineage 4 (excluding 4.3.1.1) (https://pathogen.watch/collection/ wgn6bp1c8bh6-clade-4-excluding-4311), and Typhi lineages 0-3 (https://pathogen.watch/collection/ 9o4bpn0418n3-clades-0-1-2-and-3). In addition, users can browse the full set of Typhi genomes in Pathogenwatch and select subsets of interest (e.g. by country, genotype, and/or resistance) to generate a collection including neighbour-joining tree for interactive exploration.SUPPLEMENTARY FILES : Available at https://elifesciences.org/articles/85867/figures#content. SUPPLEMENTARY FILE 1. Details of local ethical approvals provided for studies that were unpublished at the time of contributing data to this consortium project. Most data are now published, and the citations for the original studies are provided here. National surveillance programs in Chile (Maes et al., 2022), Colombia (Guevara et al., 2021), France, New Zealand, and Nigeria (Ikhimiukor et al., 2022b) were exempt from local ethical approvals as these countries allow sharing of non-identifiable pathogen sequence data for surveillance purposes. The US CDC Internal Review Board confirmed their approval was not required for use in this project (#NCEZID-ARLT- 10/ 20/21-fa687). SUPPLEMENTARY FILE 2. Line list of 13,000 genomes included in the study. SUPPLEMENTARY FILE 3. Source information recorded for genomes included in the study. ^Indicates cases included in the definition of ‘assumed acute illness’. SUPPLEMENTARY FILE 4. Summary of genomes by country. SUPPLEMENTARY FILE 5. Genotype frequencies per region (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 6. Genotype frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 7. Antimicrobial resistance (AMR) frequencies per region (N, %, 95% confidence interval; aggregated 2010–2020). SUPPLEMENTARY FILE 8. Antimicrobial resistance (AMR) frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 9. Laboratory code master list. Three letter laboratory codes assigned by the consortium.BACKGROUND : The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS : This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS : Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS : The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies.Fellowships from the European Union (funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council.https://elifesciences.org/am2024Medical MicrobiologySDG-03:Good heatlh and well-bein

Genomic analysis unveils genome degradation events and gene flux in the emergence and persistence of S. Paratyphi A lineages.

Acknowledgements: We thank Prof. Nicholas Grassly, Imperial College London, for assistance with study design and research proposal development. We gratefully acknowledge Dr. Arif M. Tanmoy, Dr. Senjuti Saha and Dr. Yogesh Hooda (CHRF, Dhaka, Bangladesh) for help with the genotyping analysis. We acknowledge Dr. Duncan Steele, Ms. Megan Carey & Dr. Supriya Kumar, Bill & Melinda Gates Foundation for their technical support throughout the study on behalf of SEFI consortium. We thank all the lab members involved in SEFI reference lab activities, especially Dr. Anushree Amladi, Ms. Baby Abirami S, Ms. Dhanabhagyam K, Ms. Beebi E, Ms. Suganya S, Ms. Udaya and Mr. Ayyanraj N, CMC Vellore implicated in phenotypic testing and stock culture maintenance. We would also like to thank all the members of SEFI consortium, Wellcome Trust Research Laboratory, CMC Vellore and core sequencing teams at the Wellcome Trust Sanger Institute for their contribution to genome sequencing. The authors thank Ms Catherine Trueman (Clinical Pharmacist, CMC Vellore) for helping with language editing.Paratyphoid fever caused by S. Paratyphi A is endemic in parts of South Asia and Southeast Asia. The proportion of enteric fever cases caused by S. Paratyphi A has substantially increased, yet only limited data is available on the population structure and genetic diversity of this serovar. We examined the phylogenetic distribution and evolutionary trajectory of S. Paratyphi A isolates collected as part of the Indian enteric fever surveillance study "Surveillance of Enteric Fever in India (SEFI)." In the study period (2017-2020), S. Paratyphi A comprised 17.6% (441/2503) of total enteric fever cases in India, with the isolates highly susceptible to all the major antibiotics used for treatment except fluoroquinolones. Phylogenetic analysis clustered the global S. Paratyphi A collection into seven lineages (A-G), and the present study isolates were distributed in lineages A, C and F. Our analysis highlights that the genome degradation events and gene acquisitions or losses are key molecular events in the evolution of new S. Paratyphi A lineages/sub-lineages. A total of 10 hypothetically disrupted coding sequences (HDCS) or pseudogenes-forming mutations possibly associated with the emergence of lineages were identified. The pan-genome analysis identified the insertion of P2/PSP3 phage and acquisition of IncX1 plasmid during the selection in 2.3.2/2.3.3 and 1.2.2 genotypes, respectively. We have identified six characteristic missense mutations associated with lipopolysaccharide (LPS) biosynthesis genes of S. Paratyphi A, however, these mutations confer only a low structural impact and possibly have minimal impact on vaccine effectiveness. Since S. Paratyphi A is human-restricted, high levels of genetic drift are not expected unless these bacteria transmit to naive hosts. However, public-health investigation and monitoring by means of genomic surveillance would be constantly needed to avoid S. Paratyphi A serovar becoming a public health threat similar to the S. Typhi of today

Lineage-defining missense mutations in <i>S</i>. Paratyphi A genomes.

Lineage-defining missense mutations in S. Paratyphi A genomes.</p

List of functional gene inactivation mutations identified between phylogenetic lineages.

List of functional gene inactivation mutations identified between phylogenetic lineages.</p

Distribution of <i>S</i>. Typhi and <i>S</i>. Paratyphi A isolates collected across the participating sites of the SEFI network.

Distribution of S. Typhi and S. Paratyphi A isolates collected across the participating sites of the SEFI network.</p

List of whole genome sequenced isolates collected from the participating sites of the SEFI network.

List of whole genome sequenced isolates collected from the participating sites of the SEFI network.</p

Antimicrobial susceptibility profile of <i>S</i>. Paratyphi A tested in the present study.

Antimicrobial susceptibility profile of S. Paratyphi A tested in the present study.</p

Rooted maximum likelihood phylogenetic tree of <i>rfb</i> loci of <i>S</i>. Paratyphi A isolates derived from the whole genome alignment by mapping against the reference genome of <i>S</i>. Paratyphi ATCC 9150 (Accession No: CP000026.1) using Snippy.

Lineages and genotypes are labelled as colour strips. Amino acid substitutions in the rfb loci are represented by heat maps. (TIF)</p