Rob Knight

Bio: Rob Knight is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Microbiome & Gut flora. The author has an hindex of 201, co-authored 1061 publications receiving 253207 citations. Previous affiliations of Rob Knight include Anschutz Medical Campus & University of Sydney.

Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes.

Abstract: The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

Trait-like vulnerability of higher-order cognition and ability to maintain wakefulness during combined sleep restriction and circadian misalignment.

Abstract: Study objectives Determine stability of individual differences in executive function, cognitive processing speed, selective visual attention, and maintenance of wakefulness during simulated sustained operations with combined sleep restriction and circadian misalignment. Methods Twenty healthy adults (eight female), aged 25.7 (±4.2 SD), body mass index (BMI) 22.3 (±2.1) kg/m2 completed an 18-day protocol twice. Participants maintained habitual self-selected 8-hour sleep schedules for 2 weeks at home prior to a 4-day laboratory visit that included one sleep opportunity per day: 8 hours on night 1, 3 hours on night 2, and 3 hours on mornings 3 and 4. After 3 days of unscheduled sleep at home, participants repeated the entire protocol. Stability and task dependency of individual differences in performance were quantified by intra-class correlation coefficients (ICC) and Kendall's Tau, respectively. Results Performance on Stroop, Visual Search, and the Maintenance of Wakefulness Test were highly consistent within individuals during combined sleep restriction and circadian misalignment. Individual differences were trait-like as indicated by ICCs (0.54-0.96) classified according to standard criteria as moderate to almost perfect. Individual differences on other performance tasks commonly reported in sleep studies showed fair to almost perfect ICCs (0.22-0.94). Kendall's rank correlations showed that individual vulnerability to sleep restriction and circadian misalignment varied by task and by metric within a task. Conclusions Consistent vulnerability of higher-order cognition and maintenance of wakefulness to combined sleep restriction and circadian misalignment has implications for the development of precision countermeasure strategies for workers performing safety-critical tasks, e.g. military, police, health care workers and emergency responders.

Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) screening among symptom-free healthcare workers.

Abstract: Transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is possible among symptom-free individuals. Patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. We screened 489 symptom-free healthcare workers for SARS-CoV-2 and found no positive results, strongly suggesting that the prevalence of SARS-CoV-2 was <1%.

Temporal, environmental, and biological drivers of the mucosal microbiome in a wild marine fish, Scomber japonicus

Abstract: Changing ocean conditions driven by anthropogenic activity may have a negative impact on fisheries by increasing stress and disease with the mucosal microbiome as a potentially important intermediate role. To understand how environment and host biology drives mucosal microbiomes in a marine fish, we surveyed five body sites (gill, skin, digesta, GI, and pyloric caeca) from 229 Pacific chub mackerel, Scomber japonicus, collected across 38 time points spanning one year from the Scripps Institution of Oceanography Pier, making this the largest and longest wild marine fish microbiome survey. Mucosal sites had unique communities significantly different from the surrounding sea water and sediment communities with over 10 times more diversity than sea water alone. Although, external surfaces such as skin and gill were more similar to sea water, digesta was similar to sediment. Both alpha and beta diversity of the skin and gill was explained by environmental and biological factors, especially sea surface temperature, chlorophyll a, and fish age, consistent with an exposure gradient relationship. We verified that seasonal microbial changes were not confounded by migrations of chub mackerel sub-populations by nanopore sequencing a 14 769 bp region of the 16 568 bp mitochondria. A cosmopolitan pathogen, Photobacterium damselae, was prevalent across multiple body sites all year, but highest in the skin, GI, and digesta between June and September. Our study evaluates the extent which the environment and host biology drives mucosal microbial ecology, establishing a baseline for long term monitoring surveys for linking environment stressors to mucosal health of wild marine fish.

Context-aware deconvolution of cell-cell communication with Tensor-cell2cell

Abstract: Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

QIIME allows analysis of high-throughput community sequencing data.

Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

Abstract: mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.

Search and clustering orders of magnitude faster than BLAST

Abstract: Motivation: Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. Results: UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Availability: Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch Contact: [email protected] Supplementary information:Supplementary data are available at Bioinformatics online.