An unusual diarrheal outbreak in the community in Eastern Thailand caused by Norovirus GII.3[P25].

BACKGROUND: Sentinel laboratory surveillance for diarrheal disease determined norovirus to be the most common cause of non-bacterial gastroenteritis in people during the COVID-19 pandemic in Thailand. An increase in patients presenting with diarrhea and vomiting in hospitals across Chanthaburi province between December 2021 and January 2022 led to the need for the identification of viral pathogens that may be responsible for the outbreak. METHODS: Fecal samples (rectal swabs or stool) from 93 patients, of which 65 patients were collected during the December 2021 to January 2022 outbreak, were collected and screened for viral infection by real-time RT-PCR. Positive samples for norovirus GII were then genotyped by targeted amplification and sequencing of partial polymerase and capsid genes. Full genome sequencing was performed from the predominant strain, GII.3[P25]. RESULTS: Norovirus was the most common virus detected in human fecal samples in this study. 39 of 65 outbreak samples (60%) and 3 of 28 (10%) non-outbreak samples were positive for norovirus genogroup II. One was positive for rotavirus, and one indicated co-infection with rotavirus and norovirus genogroups I and II. Nucleotide sequences of VP1 and RdRp gene were successfully obtained from 28 of 39 positive norovirus GII and used for dual-typing; 25/28 (89.3%) were GII.3, and 24/28 (85.7) were GII.P25, respectively. Norovirus GII.3[P25] was the predominant strain responsible for this outbreak. The full genome sequence of norovirus GII.3[P25] from our study is the first reported in Thailand and has 98.62% and 98.57% similarity to norovirus found in China in 2021 and the USA in 2022, respectively. We further demonstrate the presence of multiple co-circulating norovirus genotypes, including GII.21[P21], GII.17[P17], GII.3[P12] and GII.4[P31] in our study. CONCLUSIONS: An unusual diarrhea outbreak was found in December 2021 in eastern Thailand. Norovirus strain GII.3[P25] was the cause of the outbreak and was first detected in Thailand. The positive rate during GII.3[P25] outbreak was six times higher than sporadic cases (GII.4), and, atypically, adults were the primary infected population rather than children.

SARS-CoV-2 Variants Detection Strategies in Wastewater Samples Collected in the Bangkok Metropolitan Region.

Wastewater surveillance is considered a promising approach for COVID-19 surveillance in communities. In this study, we collected wastewater samples between November 2020 and February 2022 from twenty-three sites in the Bangkok Metropolitan Region to detect the presence of SARS-CoV-2 and its variants for comparison to standard clinical sampling. A total of 215 wastewater samples were collected and tested for SARS-CoV-2 RNA by real-time PCR with three targeted genes (N, E, and ORF1ab); 102 samples were positive (42.5%). The SARS-CoV-2 variants were determined by a multiplex PCR MassARRAY assay to distinguish four SARS-CoV-2 variants, including Alpha, Beta, Delta, and Omicron. Multiple variants of Alpha-Delta and Delta-Omicron were detected in the wastewater samples in July 2021 and January 2022, respectively. These wastewater variant results mirrored the country data from clinical specimens deposited in GISAID. Our results demonstrated that wastewater surveillance using multiple signature mutation sites for SARS-CoV-2 variant detection is an appropriate strategy to monitor the presence of SARS-CoV-2 variants in the community at a low cost and with rapid turn-around time. However, it is essential to note that sequencing surveillance of wastewater samples should be considered complementary to whole genome sequencing of clinical samples to detect novel variants.

Correction to: Analysis of anti-malarial resistance markers in pfmdr1 and pfcrt across Southeast Asia in the Tracking Resistance to Artemisinin Collaboration.

Following publication of the original article [1], one of the authors has highlighted an xml-related discrepancy concerning the author group titled 'Additional Tracking Resistance to Artemisinin Collaboration authors (TRAC Group Authorship)', listed under the Acknowledgements section.

Analysis of anti-malarial resistance markers in pfmdr1 and pfcrt across Southeast Asia in the Tracking Resistance to Artemisinin Collaboration.

BACKGROUND: Declining anti-malarial efficacy of artemisinin-based combination therapy, and reduced Plasmodium falciparum susceptibility to individual anti-malarials are being documented across an expanding area of Southeast Asia (SEA). Genotypic markers complement phenotypic studies in assessing the efficacy of individual anti-malarials. METHODS: The markers pfmdr1 and pfcrt were genotyped in parasite samples obtained in 2011-2014 at 14 TRAC (Tracking Resistance to Artemisinin Collaboration) sites in mainland Southeast Asia using a combination of PCR and next-generation sequencing methods. RESULTS: Pfmdr1 amplification, a marker of mefloquine and lumefantrine resistance, was highly prevalent at Mae Sot on the Thailand-Myanmar border (59.8% of isolates) and common (more than 10%) at sites in central Myanmar, eastern Thailand and western Cambodia; however, its prevalence was lower than previously documented in Pailin, western Cambodia. The pfmdr1 Y184F mutation was common, particularly in and around Cambodia, and the F1226Y mutation was found in about half of samples in Mae Sot. The functional significance of these two mutations remains unclear. Other previously documented pfmdr1 mutations were absent or very rare in the region. The pfcrt mutation K76T associated with chloroquine resistance was found in 98.2% of isolates. The CVIET haplotype made up 95% or more of isolates in western SEA while the CVIDT haplotype was common (30-40% of isolates) in north and northeastern Cambodia, southern Laos, and southern Vietnam. CONCLUSIONS: These findings generate cause for concern regarding the mid-term efficacy of artemether-lumefantrine in Myanmar, while the absence of resistance-conferring pfmdr1 mutations and SVMNT pfcrt haplotypes suggests that amodiaquine could be an efficacious component of anti-malarial regimens in SEA.

Protein profiling of mefloquine resistant Plasmodium falciparum using mass spectrometry-based proteomics.

Malaria is a mosquito borne infectious disease caused by protozoa of genus Plasmodium. There are five species of Plasmodium that are found to infect humans. Plasmodium falciparum can cause severe malaria leading to higher morbidity and mortality of malaria than the other four species. Antimalarial resistance is the major obstacle to control malaria. Mefloquine was used in combination with Artesunate for uncomplicated P. falciparum in South East Asia and it has developed and established mefloquine resistance in this region. Here, gel-enhanced liquid chromatography/tandem mass spectrometry (GeLC-MS/MS)-based proteomics and label-free quantification were used to explore the protein profiles of mefloquine-sensitive and -induced resistant P. falciparum. A Thai P. falciparum isolate (S066) was used as a model in this research. Our data revealed for the first time that 69 proteins exhibited at least 2-fold differences in their expression levels between the two parasite lines. Of these, 36 were up-regulated and 33 were down-regulated in the mefloquine-resistant line compared with the mefloquine-sensitive line. These findings are consistent with those of past studies, where the multidrug resistance protein Pgh1 showed an up-regulation pattern consistent with that expected from its average 3-copy pfmdr1 gene number. Pgh1 and eight other up-regulated proteins (i.e., histo-aspartyl protease protein, exportin 1, eukaryotic translation initiation factor 3 subunit 8, peptidyl-prolyl cis-trans isomerase, serine rich protein homologue, exported protein 1, ATP synthase beta chain and phospholipid scramblase 1) were further validated for their expression levels using reverse transcriptase quantitative real-time PCR. The data support the up-regulation status in the mefloquine-resistant parasite line of all the candidate genes referred to above. Therefore, GeLC-MS/MS-based proteomics combined with label-free quantification is a reliable approach for exploring mefloquine resistance biomarkers in P. falciparum. Identification of these proteins leads to better understanding of mefloquine resistant mechanisms in malaria parasites.