An In-Home Withdrawal Service for individuals with low-to-moderate substance dependence: implementation and program evaluation.

Background Sonder's In-Home Withdrawal Service (IHWS) has been providing a unique home-based, multidisciplinary, wraparound withdrawal option for people with low-to-moderate levels of substance dependence since September 2019. This paper provides an evaluation of the service's overall impact on reducing substance use among clients through the delivery of this innovative service model. The evaluation explores the acceptability and feasibility of the service via client, stakeholder, and staff perspectives.

Endoplasmic reticulum stress sensor IRE1α propels neutrophil hyperactivity in lupus.

Neutrophils amplify inflammation in lupus through the release of neutrophil extracellular traps (NETs). The endoplasmic reticulum stress sensor inositol-requiring enzyme 1 α (IRE1α) has been implicated as a perpetuator of inflammation in various chronic diseases; however, IRE1α has been little studied in relation to neutrophil function or lupus pathogenesis. Here, we found that neutrophils activated by lupus-derived immune complexes demonstrated markedly increased IRE1α ribonuclease activity.

Exploiting high-throughput cell line drug screening studies to identify candidate therapeutic agents in head and neck cancer.

Background: There is an urgent need for better therapeutics in head and neck squamous cell cancer (HNSCC) to improve survival and decrease treatment morbidity. Recent advances in high-throughput drug screening techniques and next-generation sequencing have identified new therapeutic targets in other cancer types, but an HNSCC-specific study has not yet been carried out. We have exploited data from two large-scale cell line projects to clearly describe the mutational and copy number status of HNSCC cell lines and identify candidate drugs with elevated efficacy in HNSCC.

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis.

Background: Experimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments.

Comparative meta-RNA-seq of the vaginal microbiota and differential expression by Lactobacillus iners in health and dysbiosis.

Background: Bacterial vaginosis (BV), the most common vaginal condition of reproductive-aged women, is associated with a highly diverse and heterogeneous microbiota. Here we present a proof-of-principle analysis to uncover the function of the microbiota using meta-RNA-seq to uncover genes and pathways that potentially differentiate healthy vaginal microbial communities from those in the dysbiotic state of bacterial vaginosis (BV).

Results: The predominant organism, Lactobacillus iners, was present in both conditions and showed a differing expression profile in BV compared to healthy.

ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq.

Experimental variance is a major challenge when dealing with high-throughput sequencing data. This variance has several sources: sampling replication, technical replication, variability within biological conditions, and variability between biological conditions. The high per-sample cost of RNA-Seq often precludes the large number of experiments needed to partition observed variance into these categories as per standard ANOVA models.

Divalent metal ion differentially regulates the sequential nicking reactions of the GIY-YIG homing endonuclease I-BmoI.

Homing endonucleases are site-specific DNA endonucleases that function as mobile genetic elements by introducing double-strand breaks or nicks at defined locations. Of the major families of homing endonucleases, the modular GIY-YIG endonucleases are least understood in terms of mechanism. The GIY-YIG homing endonuclease I-BmoI generates a double-strand break by sequential nicking reactions during which the single active site of the GIY-YIG nuclease domain must undergo a substantial reorganization.

Estimating the evidence of selection and the reliability of inference in unigenic evolution.

Background: Unigenic evolution is a large-scale mutagenesis experiment used to identify residues that are potentially important for protein function. Both currently-used methods for the analysis of unigenic evolution data analyze 'windows' of contiguous sites, a strategy that increases statistical power but incorrectly assumes that functionally-critical sites are contiguous. In addition, both methods require the questionable assumption of asymptotically-large sample size due to the presumption of approximate normality.

Microbiome profiling by illumina sequencing of combinatorial sequence-tagged PCR products.

We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end.

Deep sequencing of the vaginal microbiota of women with HIV.

Background: Women living with HIV and co-infected with bacterial vaginosis (BV) are at higher risk for transmitting HIV to a partner or newborn. It is poorly understood which bacterial communities constitute BV or the normal vaginal microbiota among this population and how the microbiota associated with BV responds to antibiotic treatment.

Methods And Findings: The vaginal microbiota of 132 HIV positive Tanzanian women, including 39 who received metronidazole treatment for BV, were profiled using Illumina to sequence the V6 region of the 16S rRNA gene.

Identifying and seeing beyond multiple sequence alignment errors using intra-molecular protein covariation.

Background: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment.

Mutual information is critically dependent on prior assumptions: would the correct estimate of mutual information please identify itself?

Motivation: Mutual information (MI) is a quantity that measures the dependence between two arbitrary random variables and has been repeatedly used to solve a wide variety of bioinformatic problems. Recently, when attempting to quantify the effects of sampling variance on computed values of MI in proteins, we encountered striking differences among various novel estimates of MI. These differences revealed that estimating the 'true' value of MI is not a straightforward procedure, and minor variations of assumptions yielded remarkably different estimates.

Functionally compensating coevolving positions are neither homoplasic nor conserved in clades.

We demonstrated that a pair of positions in phosphoglycerate kinase that score highly by three nonparametric covariation measures are important for function even though the positions can be occupied by aliphatic, aromatic, or charged residues. Examination of these pairs suggested that the majority of the covariation scores could be explained by within-clade conservation. However, an analysis of diversity showed that the conservation within clades of covarying pairs was indistinguishable from pairs of positions that do not covary, thus ruling out both clade conservation and extensive homoplasy as means to identify covarying positions.

A unified genetic, computational and experimental framework identifies functionally relevant residues of the homing endonuclease I-BmoI.

Insight into protein structure and function is best obtained through a synthesis of experimental, structural and bioinformatic data. Here, we outline a framework that we call MUSE (mutual information, unigenic evolution and structure-guided elucidation), which facilitated the identification of previously unknown residues that are relevant for function of the GIY-YIG homing endonuclease I-BmoI. Our approach synthesizes three types of data: mutual information analyses that identify co-evolving residues within the GIY-YIG catalytic domain; a unigenic evolution strategy that identifies hyper- and hypo-mutable residues of I-BmoI; and interpretation of the unigenic and co-evolution data using a homology model.

The SWI/SNF protein ATRX co-regulates pseudoautosomal genes that have translocated to autosomes in the mouse genome.

Background: Pseudoautosomal regions (PAR1 and PAR2) in eutherians retain homologous regions between the X and Y chromosomes that play a critical role in the obligatory X-Y crossover during male meiosis. Genes that reside in the PAR1 are exceptional in that they are rich in repetitive sequences and undergo a very high rate of recombination. Remarkably, murine PAR1 homologs have translocated to various autosomes, reflecting the complex recombination history during the evolution of the mammalian X chromosome.

Site-specific evolutionary rates in proteins are better modeled as non-independent and strictly relative.

Motivation: In a nucleotide or amino acid sequence, not all sites evolve at the same rate, due to differing selective constraints at each site. Currently in computational molecular evolution, models incorporating rate heterogeneity always share two assumptions. First, the rate of evolution at each site is assumed to be independent of every other site.

Biochemical and functional evidence of p53 homology is inconsistent with molecular phylogenetics for distant sequences.

The tumor suppressor p53 is mutated in approximately 50% of all human cancer cases worldwide. It is commonly assumed that the phylogenetic history of this important tumor suppressor has been thoroughly studied; however, few detailed studies of the entire extended p53 protein family have been reported, and none comprehensively and simultaneously consider functional, molecular, and phylogenetic data. Herein we examine a diverse collection of reported p53-like protein sequences, including representatives from the arthropods, nematodes, and protists, with the goal of answering several important questions.

Gaussian quadrature formulae for arbitrary positive measures.

We present computational methods and subroutines to compute Gaussian quadrature integration formulas for arbitrary positive measures. For expensive integrands that can be factored into well-known forms, Gaussian quadrature schemes allow for efficient evaluation of high-accuracy and -precision numerical integrals, especially compared to general ad hoc schemes. In addition, for certain well-known density measures (the normal, gamma, log-normal, Student's t, inverse-gamma, beta, and Fisher's F) we present exact formulae for computing the respective quadrature scheme.

Sequence signatures and the probabilistic identification of proteins in the Myc-Max-Mad network.

Accurate identification of specific groups of proteins by their amino acid sequence is an important goal in genome research. Here we combine information theory with fuzzy logic search procedures to identify sequence signatures or predictive motifs for members of the Myc-Max-Mad transcription factor network. Myc is a well known oncoprotein, and this family is involved in cell proliferation, apoptosis, and differentiation.

Solving the protein sequence metric problem.

Biological sequences are composed of long strings of alphabetic letters rather than arrays of numerical values. Lack of a natural underlying metric for comparing such alphabetic data significantly inhibits sophisticated statistical analyses of sequences, modeling structural and functional aspects of proteins, and related problems. Herein, we use multivariate statistical analyses on almost 500 amino acid attributes to produce a small set of highly interpretable numeric patterns of amino acid variability.