The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

SummaryWe report the first local transmission of the Delta SARS-CoV-2 variant in mainland China. All 167 infections could be traced back to the first index case. The investigation on daily sequential PCR testing of the quarantined subjects indicated the viral load of the first positive test of Delta infections was ∼1000 times higher than that of the 19A/19B strains infections back in the initial epidemic wave of 2020, suggesting the potential faster viral replication rate and more infectiousness of the Delta variant at the early stage of the infection. The 126 high-quality sequencing data and reliable epidemiological data indicated some minor intra-host single nucleotide variants (iSNVs) could be transmitted between hosts and finally fixed in the virus population during the outbreak. The minor iSNVs transmission between donor-recipient contribute at least 4 of 31 substitutions identified in the outbreak suggesting some iSNVs could quickly arise and reach fixation when the virus spread rapidly. Disease control measures, including the frequency of population testing, quarantine in pre-symptomatic phase and enhancing the genetic surveillance should be adjusted to account for the increasing prevalence of the Delta variant at global level.

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BackgroundEpistasis is recognized ubiquitous in the genetic architecture of complex traits such as disease susceptibility. Experimental studies in model organisms have revealed extensive evidence of biological interactions among genes. Meanwhile, statistical and computational studies in human populations have suggested non-additive effects of genetic variation on complex traits. Although these studies form a baseline for understanding the genetic architecture of complex traits, to date they have only considered interactions among a small number of genetic variants. Our goal here is to use network science to determine the extent to which non-additive interactions exist beyond small subsets of genetic variants. We infer statistical epistasis networks to characterize the global space of pairwise interactions among approximately 1500 Single Nucleotide Polymorphisms (SNPs) spanning nearly 500 cancer susceptibility genes in a large population-based study of bladder cancer.ResultsThe statistical epistasis network was built by linking pairs of SNPs if their pairwise interactions were stronger than a systematically derived threshold. Its topology clearly differentiated this real-data network from networks obtained from permutations of the same data under the null hypothesis that no association exists between genotype and phenotype. The network had a significantly higher number of hub SNPs and, interestingly, these hub SNPs were not necessarily with high main effects. The network had a largest connected component of 39 SNPs that was absent in any other permuted-data networks. In addition, the vertex degrees of this network were distinctively found following an approximate power-law distribution and its topology appeared scale-free.ConclusionsIn contrast to many existing techniques focusing on high main-effect SNPs or models of several interacting SNPs, our network approach characterized a global picture of gene-gene interactions in a population-based genetic data. The network was built using pairwise interactions, and its distinctive network topology and large connected components indicated joint effects in a large set of SNPs. Our observations suggested that this particular statistical epistasis network captured important features of the genetic architecture of bladder cancer that have not been described previously.

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Gut microbiota plays important roles in the host health. The host and symbiotic gut microbiota coproduce a large number of metabolites during the metabolism of food and xenobiotics. The analysis of fecal metabolites can provide a noninvasive manner to study the outcome of the host-gut microbiota interaction. Herein, we reported the comprehensive profiling of fecal metabolome of mice by an integrated chemical isotope labeling combined with liquid chromatography-mass spectrometry (CIL-LC-MS) analysis. The metabolites are categorized into several submetabolomes based on the functional moieties (i.e., carboxyl, carbonyl, amine, and thiol) and then analysis of the individual submetabolome was performed. The combined data from the submetabolome form the metabolome with relatively high coverage. To this end, we synthesized stable isotope labeling reagents to label metabolites with different groups, including carboxyl, carbonyl, amine, and thiol groups. We detected 2302 potential metabolites, among which, 1388 could be positively or putatively identified in feces of mice. We then further confirmed 308 metabolites based on our established library of chemically labeled standards and tandem mass spectrometry analysis. With the identified metabolites in feces of mice, we established mice fecal metabolome database, which can be used to readily identify metabolites from feces of mice. Furthermore, we discovered 211 fecal metabolites exhibited significant difference between Alzheimer's disease (AD) model mice and wild type (WT) mice, which suggests the close correlation between the fecal metabolites and AD pathology and provides new potential biomarkers for the diagnosis of AD.

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Background: The Delta variant of SARS-CoV-2 has become predominant globally. We evaluated the transmission dynamics and epidemiological characteristics of the Delta variant in an outbreak in southern China. Methods: Data on confirmed cases and their close contacts were retrospectively collected from the outbreak that occurred in Guangdong, China in May-June 2021. Key epidemiological parameters, temporal trend of viral loads and secondary attack rates were estimated and compared between the Delta variant and the wild-type SARS-CoV-2 virus. We also evaluated the association of vaccination with viral load and transmission. Results: We identified 167 patients infected with the Delta variant in the Guangdong outbreak. The mean estimates of the latent period and the incubation period were 4.0 days and 5.8 days, respectively. A relatively higher viral load was observed in Delta cases than in wild-type infections. The secondary attack rate among close contacts of Delta cases was 1.4%, and 73.9% (95% confidence interval: 67.2%, 81.3%) of the transmissions occurred before onset. Index cases without vaccination (OR: 2.84, 95% confidence interval: 1.19, 8.45) or with one dose of vaccination (OR: 6.02, 95% confidence interval: 2.45, 18.16) were more likely to transmit infection to their contacts than those who had received 2 doses of vaccination. Discussion: Patients infected with the Delta variant had more rapid symptom onset. The shorter and time-varying serial interval should be accounted in estimation of reproductive numbers. The higher viral load and higher risk of pre-symptomatic transmission indicated the challenges in control of infections with the Delta variant.