Open access
Epidemiology
15 April 2021

Near-Complete Genome Sequences of Eight Human Astroviruses Recovered from Diarrheal Stool Samples of Hospitalized Children in Coastal Kenya in 2019

ABSTRACT

Here, using a sequence-independent sequencing approach (M. V. Phan, P. Hong Anh, N. Van Cuong, B. Oude Munnink, et al., Virus Evol 2:vew027, 2016, https://doi.org/10.1093/ve/vew027), we determined human astrovirus (HAstV) genome sequences from eight diarrheal stool samples collected in coastal Kenya in 2019. Phylogenetic analysis identified the following 4 genotypes: HAstV-1 (n = 4), HAstV-2 (n = 1), HAstV-3 (n = 1), and HAstV-5 (n = 2).

ANNOUNCEMENT

Human astroviruses (HAstVs) (family Astroviridae) are nonenveloped, 7-kb positive-sense, single-stranded RNA genome viruses (1) and are among the top 5 viral causes of childhood diarrhea globally (2). HAstV clinical isolates are classified into classic HAstVs (HAstV-1 to HAstV-8), HAstV-MLB, and HAstV-VA/HMO (1).
In Kenya and other African settings, HAstV positivity in children with diarrhea as one of their illness symptoms ranges from 2.7% to 10.3% (35). To date, there are no complete or near-complete (≥90% genome coverage) HAstV genome sequences from East Africa in the GenBank database (6). Analysis of HAstV genome sequences may facilitate optimization of molecular diagnostics and tracking the spread of HAstVs (7). Here, we utilized sequence-independent single-primer amplification (SISPA) sequencing to generate new HAstV genome sequences from positive reverse transcription-quantitative PCR (RT-PCR) (5) samples collected from children hospitalized with diarrhea in Kilifi, Kenya.
Total nucleic acid (TNA) was extracted from the 10 stool specimens using the QIAamp fast DNA stool minikit (Qiagen, Manchester, United Kingdom). The TNA was treated with Turbo DNase (Invitrogen, Carlsbad, CA), and first-strand synthesis was performed with FR26RV-ENDOH primers (8). Second-strand DNA synthesis was performed with Klenow fragment 3′ to 5′ exo- (New England BioLabs). To achieve a nonselective nucleic acid amplification, double-stranded DNA (dsDNA) was primed with the FR20RV primer (5′-GCCGGAGCTCTGCAGATATC-3′), complementary to the FR26RV-ENDOH primers at the 5′ end (9), and amplified using SuperScript III with the Platinum Taq DNA polymerase kit (Qiagen) as per the manufacturer’s protocol. The PCR product was used to prepare Illumina barcoded libraries using the Illumina DNA Flex kit and sequenced in one run using the Illumina MiSeq machine generating 75-bp paired-end reads. Sequencing adapters and low-quality bases (Phred score,<30) were trimmed/removed from the short-read data using QUASR v.7.03 (10). Reference HAstV-1, HAstV-2, HAstV-3, and HAstV-5 genome sequences (GenBank accession numbers JF327666, KF039911, MN444721, and MF684776, respectively) were used for reference-guided assembly and to transfer annotations to the assembled genomes using the inbuilt Geneious mapper and annotation tools, respectively, on Geneious Prime v.2019.2.3 (11). MAFFT v.7.313 (12) was used for nucleotide coding sequence alignment, and maximum likelihood phylogenies were reconstituted in IQ-Tree v.2.0.6 (13) with standard model selection. Written informed consent for study participation was obtained from parents/guardians of the enrolled children, and the study protocol was approved by the KEMRI Scientific and Ethics Review Unit (SSC 2861 and SERU CGMRC/113/3624).
Patient demographics and sequencing output characteristics for the 10 samples are provided in Table 1. Eight samples yielded a consensus sequence covering >90% of the HAstV full-length genome. A maximum likelihood phylogeny of these eight near-complete genomes, including all publicly available HAstV genomes, is shown in Fig. 1. The new Kilifi sequences clustered with four different types of classical HAstVs, namely, HAstV-1 (n = 4), HAstV-2 (n =1), HAstV-3 (n = 1), and HAstV-5 (n = 2). Both the HAstV-1 (n = 4) and HAstV-5 (n = 2) genomes had > 99% nucleotide similarity within their respective types. These new near-complete HAstV genomes from coastal Kenya increase available HAstV genomic data to support future molecular studies and local diagnostic methods.
FIG 1
FIG 1 Maximum likelihood phylogenetic tree based on the open reading frame (ORF) sequences of the eight classical HAstVs (>90% genome coverage) identified in this study and representative strains from GenBank. The tree was constructed using IQ-Tree v.2.0.6 (13) with standard model selection. Bar indicates nucleotide substitutions per site. Red and black show HAstVs identified in this study and globally, respectively.
TABLE 1
TABLE 1 Characteristics of human astrovirus genomes from coastal Kenya in 2019
StrainTypeCollection date (day-mo-yr)CT valueaAge (mo)SexSymptom(s)bGenome length (ntc)Total no. of raw readsNo. of mapped readsAvg depthdGenome coverage (%)eGC content (%)Pairwise identity to reference (%)GenBank accession no.Reference genome length (nt)
KLF/ASV/001HAstV113/4/201919.525FemaleD + V6,1152,014,832179,07613890.2444.397.2MW4850386,776
KLF/ASV/008HAstV126/4/201922.823MaleD + V6,7761,297,2225,67353100.0044.997.4MW4850406,776
KLF/ASV/010HAstV118/7/201922.515MaleD + V6,3981,317,294878994.4247.997.2MW4850416,776
KLF/ASV/006HAstV123/7/201921.48MaleD + V6,6983,015,0063,7443998.8545.097.3MW4850396,776
KLF/ASV/009HAstV110/6/201924.027FemaleD + V5,3421,912,848388578.84   6,776
KLF/ASV/004HAstV119/6/201922.210FemaleD + V4,7881,952,244195370.66   6,776
KLF/ASV/005HAstV219/6/201923.912MaleD + V6,7251,581,10613,12115899.2244.290.3MW4850426,778
KLF/ASV/007HAstV315/4/201926.222FemaleD6,7472,302,64010,13710099.3744.094.1MW4850436,790
KLF/ASV/002HAstV51/6/201924.39FemaleD6,6662,906,0601,7691897.9943.698.3MW4850446,803
KLF/ASV/003HAstV51/6/201922.424MaleD + V6,3613,046,3801,1881393.5043.798.5MW4850456,803
a
The real-time RT-PCR (rRT-PCR) assay, including primers and probe sequences used for HAstV detection, has been described previously (6). CT, cycle threshold.
b
Objective evidence of a diarrheal disease. D, diarrhea; V, vomiting.
C
nt, nucleotide.
d
Calculated by dividing the per-position coverage output by respective genome length.
e
Calculated by dividing the genome length by the respective reference genome length.

Data availability.

The raw sequence data were deposited in the Sequence Read Archive (SRA) under BioProject accession number PRJNA692787 and BioSample accession numbers SAMN17370496 to SAMN17370503. The genome sequences generated here were deposited in GenBank under accession numbers MW485038 to MW485045.

ACKNOWLEDGMENTS

We thank the study participants who provided the material we analyzed here.
This study was funded by The Wellcome Trust (102975 and 203077) and the Initiative to Develop African Research Leaders (IDeAL) through the DELTAS Africa Initiative (DEL-15-003). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS) Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from The Wellcome Trust (107769/Z/10/Z) and the UK government.
The views expressed in this publication are ours and not necessarily those of AAS, NEPAD Agency, The Wellcome Trust, or the UK government.
This paper is published with the permission of the director of KEMRI.

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Information & Contributors

Information

Published In

cover image Microbiology Resource Announcements
Microbiology Resource Announcements
Volume 10Number 1515 April 2021
eLocator: 10.1128/mra.00162-21
Editor: Jelle Matthijnssens, KU Leuven

History

Received: 11 February 2021
Accepted: 16 March 2021
Published online: 15 April 2021

Contributors

Authors

Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
My V. T. Phan
UK Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
Zaydah R. de Laurent
Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
Matthew Cotten
UK Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
D. James Nokes
Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
School of Life Sciences and Zeeman Institute (SBIDER), University of Warwick, Coventry, United Kingdom
Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
School of Health and Human Sciences, Pwani University, Kilifi, Kenya

Editor

Jelle Matthijnssens
Editor
KU Leuven

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