BackgroundMalaria still poses one of the major threats to human health. Development of effective antimalarial drugs has decreased this threat; however, the emergence of drug-resistant Plasmodium falciparum, a cause of Malaria, is disconcerting. The antimalarial drug chloroquine has been effectively used, but resistant parasites have spread worldwide. Interestingly, the withdrawal of the drug reportedly leads to an increased population of susceptible parasites in some cases. We examined the prevalence of genomic polymorphisms in a malaria parasite P. falciparum, associated with resistance to an antimalarial drug chloroquine, after the withdrawal of the drug from Indonesia.ResultsBlood samples were collected from 95 malaria patients in North Sulawesi, Indonesia, in 2010. Parasite DNA was extracted and analyzed by polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) for pfcrt and pfmdr1. In parallel, multiplex amplicon sequencing for the same genes was carried out with Illumina MiSeq. Of the 59 cases diagnosed as P. falciparum infection by microscopy, PCR–RFLP analysis clearly identified the genotype 76T in pfcrt in 44 cases. Sequencing analysis validated the identified genotypes in the 44 cases and demonstrated that the haplotype in the surrounding genomic region was exclusively SVMNT. Results of pfmdr1 were successfully obtained for 51 samples, where the genotyping results obtained by the two methods were completely consistent. In pfmdr1, the 86Y mutant genotype was observed in 45 cases (88.2%).ConclusionsOur results suggest that the prevalence of the mutated genotypes remained dominant even 6 years after the withdrawal of chloroquine from this region. Diversified haplotype of the resistance-related locus, potentially involved in fitness costs, unauthorized usage of chloroquine, and/or a short post-withdrawal period may account for the observed high persistence of prevalence.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-017-2468-1) contains supplementary material, which is available to authorized users.
Immune responses are different between individuals and personal health histories and unique environmental conditions should collectively determine the present state of immune cells. However, the molecular systems underlying such heterogeneity remain elusive. Here, we conducted a systematic time-lapse single-cell analysis, using 171 single-cell libraries and 30 mass cytometry datasets intensively for seven healthy individuals. We found substantial diversity in immune-cell profiles between different individuals. These patterns showed daily fluctuations even within the same individual. Similar diversities were also observed for the T-cell and B-cell receptor repertoires. Detailed immune-cell profiles at healthy statuses should give essential background information to understand their immune responses, when the individual is exposed to various environmental conditions. To demonstrate this idea, we conducted the similar analysis for the same individuals on the vaccination of influenza and SARS-CoV-2. In fact, we detected distinct responses to vaccines between individuals, although key responses are common. Single-cell immune-cell profile data should make fundamental data resource to understand variable immune responses, which are unique to each individual.
Nucleic acid test (NAT), most typically quantitative PCR, is one of the standard methods for species specific flavivirus diagnosis. Semi-comprehensive NATs such as pan-flavivirus PCR which covers genus Flavivirus are also available; however, further specification by sequencing is required for species level differentiation. In this study, a semi-comprehensive detection system that allows species differentiation of flaviviruses was developed by integration of the pan-flavivirus PCR and Nanopore sequencing. In addition, a multiplexing method was established by adding index sequences through the PCR with a streamlined bioinformatics pipeline. This enables defining cut-off values for observed read counts. In the laboratory setting, this approach allowed the detection of up to nine different flaviviruses. Using clinical samples collected in Vietnam and Brazil, seven different flaviviruses were also detected. When compared to a commercial NAT, the sensitivity and specificity of our system were 66.7% and 95.4%, respectively. Conversely, when compared to our system, the sensitivity and specificity of the commercial NAT were 57.1% and 96.9%, respectively. In addition, Nanopore sequencing detected more positive samples (n = 8) compared to the commercial NAT (n = 6). Collectively, our study has established a semi-comprehensive sequencing-based diagnostic system for the detection of flaviviruses at extremely affordable costs, considerable sensitivity, and only requires simple experimental methods.
It is believed that immune responses are different between individuals and at different times. In addition, personal health histories and unique environmental conditions should collectively determine the present state of immune cells. However, the cellular and molecular system mechanisms underlying such heterogeneity remain largely elusive. In this study, we conducted a systematic time-lapse single-cell analysis, using 171 single-cell libraries and 30 mass cytometry datasets intensively for seven healthy individuals. We found substantial diversity in immune cell populations and their gene expression patterns between different individuals. These patterns showed daily fluctuations even within the same individual spending a usual life. Similar diversities were also observed for the T cell receptor and B cell receptor repertoires. Detailed immune cell profiles at healthy statuses should give an essential background information to understand their immune responses, when the individual is exposed to various environmental conditions. To demonstrate this idea, we conducted the similar analysis for the same individuals on the vaccination of Influenza and SARS-CoV-2, since the date and the dose of the antigens are well-defined in these cases. In fact, we found that the distinct responses to vaccines between individuals, althougth key responses are common. Single cell immune cell profile data should make fundamental data resource to understand variable immune responses, which are unique to each individual.
The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single‐cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID‐19) has recently become one of the most remarkable examples of the necessity of in‐depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current “state of the art” in single‐cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID‐19.
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