http://bartellab.wi.mit.edu/publication_reprints/Bartel_Cell09.pdf

MicroRNAs: Target Recognition and Regulatory Functions

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

MicroRNAs (miRNAs) are small endogenous RNAs that pair to sites in mRNAs to direct post-transcriptional repression. Many sites that match the miRNA seed (nucleotides 2–7), particularly those in 3 untranslated regions (3UTRs), are preferentially conserved. Here, we overhauled our tool for finding preferential conservation of sequence motifs and applied it to the analysis of human 3UTRs, increasing by nearly threefold the detected number of preferentially conserved miRNA target sites. The new tool more efficiently incorporates new genomes and more completely controls for background conservation by accounting for mutational biases, dinucleotide conservation rates, and the conservation rates of individual UTRs. The improved background model enabled preferential conservation of a new site type, the “offset 6mer,” to be detected. In total, >45,000 miRNA target sites within human 3UTRs are conserved above background levels, and >60% of human protein-coding genes have been under selective pressure to maintain pairing to miRNAs. Mammalian-specific miRNAs have far fewer conserved targets than do the more broadly conserved miRNAs, even when considering only more recently emerged targets. Although pairing to the 3 end of miRNAs can compensate for seed mismatches, this class of sites constitutes less than 2% of all preferentially conserved sites detected. The new tool enables statistically powerful analysis of individual miRNA target sites, with the probability of preferentially conserved targeting (PCT) correlating with experimental measurements of repression. Our expanded set of target predictions (including conserved 3-compensatory sites), are available at the TargetScan website, which displays the PCT for each site and each predicted target.

/pdf/most-mammalian-mrnas-are-conserved-targets-of-micrornas-3olkivgkza.pdf

Most mammalian mRNAs are conserved targets of microRNAs

Proteins are built by using the information contained in molecules of messenger RNA (mRNA). Cells have several ways of controlling the amounts of different proteins they make. For example, a so-called ‘microRNA’ molecule can bind to an mRNA molecule to cause it to be more rapidly degraded and less efficiently used, thereby reducing the amount of protein built from that mRNA. Indeed, microRNAs are thought to help control the amount of protein made from most human genes, and biologists are working to predict the amount of control imparted by each microRNA on each of its mRNA targets. All RNA molecules are made up of a sequence of bases, each commonly known by a single letter—‘A’, ‘U’, ‘C’ or ‘G’. These bases can each pair up with one specific other base—‘A’ pairs with ‘U’, and ‘C’ pairs with ‘G’. To direct the repression of an mRNA molecule, a region of the microRNA known as a ‘seed’ binds to a complementary sequence in the target mRNA. ‘Canonical sites’ are regions in the mRNA that contain the exact sequence of partner bases for the bases in the microRNA seed. Some canonical sites are more effective at mRNA control than others. ‘Non-canonical sites’ also exist in which the pairing between the microRNA seed and mRNA does not completely match. Previous work has suggested that many non-canonical sites can also control mRNA degradation and usage. Agarwal et al. first used large experimental datasets from many sources to investigate microRNA activity in more detail. As expected, when mRNAs had canonical sites that matched the microRNA, mRNA levels and usage tended to drop. However, no effect was observed when the mRNAs only had recently identified non-canonical sites. This suggests that microRNAs primarily bind to canonical sites to control protein production. Based on these results, Agarwal et al. further developed a statistical model that predicts the effects of microRNAs binding to canonical sites. The updated model considers 14 different features of the microRNA, microRNA site, or mRNA—including the mRNA sequence around the site—to predict which sites within mRNAs are most effectively targeted by microRNAs. Tests showed that Agarwal et al.'s model was as good as experimental approaches at identifying the effective target sites, and was better than existing computational models. The model has been used to power the latest version of a freely available resource called TargetScan, and so could prove a valuable resource for researchers investigating the many important roles of microRNAs in controlling protein production.

/pdf/predicting-effective-microrna-target-sites-in-mammalian-4ivmgdccgc.pdf

Predicting effective microRNA target sites in mammalian mRNAs

MicroRNAs constitute a large family of small, approximately 21-nucleotide-long, non-coding RNAs that have emerged as key post-transcriptional regulators of gene expression in metazoans and plants. In mammals, microRNAs are predicted to control the activity of approximately 30% of all protein-coding genes, and have been shown to participate in the regulation of almost every cellular process investigated so far. By base pairing to mRNAs, microRNAs mediate translational repression or mRNA degradation. This Review summarizes the current understanding of the mechanistic aspects of microRNA-induced repression of translation and discusses some of the controversies regarding different modes of microRNA function.

/pdf/mechanisms-of-post-transcriptional-regulation-by-micrornas-qzhray7sm6.pdf

Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?

Palmoplantar keratodermas (PPKs, OMIM #144200) refers to a large phenotypically and genetically heterogeneous group of keratinization disorders characterized by marked hyperkeratosis on the surface of palms and soles. Punctate PPK (PPKP) features multiple hyperkeratotic papules that develop in early adolescence or later and are irregularly distributed on the palms and soles. The disease is clinically classified into three autosomal dominant subtypes: PPKP1 (OMIM #148600, 614936) characterized by multiple tiny punctate keratoses and caused by mutations in the AAGAB or COL14A1 genes; PPKP2 (OMIM #175860) which features tiny hyperkeratotic spinous papules and PPKP3 or acrokeratoelastoidosis (AKE, OMIM # 101850) which manifests with small hyperkeratotic papules located over the peripheral margins of the palms and soles and is typically associated with degeneration of elastic fibers on histology. The molecular etiology of PPKP2 and AKE remains unknown. This article is protected by copyright. All rights reserved.

Punctate palmoplantar keratoderma: an unusual mutation causing an unusual phenotype

Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of BSI patients at high risk of poor outcomes is important for earlier decision making and effective patient stratification. We developed electronic medical record-based machine learning models that predict patient outcomes of BSI. The area under the receiver-operating characteristics curve was 0.82 for a full featured inclusive model, and 0.81 for a compact model using only 25 features. Our models were trained using electronic medical records that include demographics, blood tests, and the medical and diagnosis history of 7889 hospitalized patients diagnosed with BSI. Among the implications of this work is implementation of the models as a basis for selective rapid microbiological identification, toward earlier administration of appropriate antibiotic therapy. Additionally, our models may help reduce the development of BSI and its associated adverse health outcomes and complications.

/pdf/predicting-bloodstream-infection-outcome-using-machine-1p3n10j0at.pdf

Predicting bloodstream infection outcome using machine learning.

Summary Glioblastoma (GBM) is the most aggressive form of glioma, with poor prognosis exhibited by most patients, and a median survival time of less than two years. To examine survival-associated patterns, we assembled a cohort of 87 GBM patients whose survival ranges from less than 3 months and up to 10 years, most of which are not bearing isocitrate-dehyderogenase (IDH)-1 mutation and did not undergo prior treatment. We integrated high-resolution mass-spectrometry proteomics and RNA-sequencing to examine the yet unresolved proteomic contribution to poor patient outcome, and compared it to the more established transcriptomic contribution and to published single-cell RNA-sequencing data. Discovering both layer-specific and shared processes, we found that immune, metabolic and developmental processes distinguish short and long survival periods. Additionally, we observed a significant discrepancy in tumor classification between expression layers. Overall, our integrative findings establish proteomic heterogeneity in GBM as a gateway to understanding poor patient survival.

/pdf/proteogenomics-of-glioblastoma-associates-molecular-patterns-2wqvv8ibv3.pdf

Proteogenomics of glioblastoma associates molecular patterns with survival

Oral microbiota signatures in post-traumatic stress disorder (PTSD) veterans

The concentration of SARS-CoV-2-specific serum antibodies, elicited by vaccination or infection, is a primary determinant of anti-viral immunity, which correlates with protection against infection and COVID-19. Serum samples were obtained from 25 897 participants and assayed for anti-SARS-CoV-2 spike protein RBD IgG antibodies. The cohort was composed of newly vaccinated BNT162b2 recipients, in the first month or 6 months after vaccination, COVID-19 patients and a general sample of the Israeli population. Antibody levels of BNT162b2 vaccine recipients were negatively correlated with age, with a prominent decrease in recipients over 55 years old, which was most significant in males. This trend was observable within the first month and 6 months after vaccination, while younger participants were more likely to maintain stable levels of serum antibodies. The antibody concentration of participants previously infected with SARS-CoV-2 was lower than the vaccinated and had a more complex, non-linear relation to age, sex and COVID-19 symptoms. Taken together, our data supports age and sex as primary determining factors for both the magnitude and durability of humoral response to SARS-CoV-2 infection and the COVID-19 vaccine. Our results could inform vaccination policies, prioritizing the most susceptible populations for repeated vaccination. 

Noam Shomron

Papers

Punctate palmoplantar keratoderma: an unusual mutation causing an unusual phenotype

Predicting bloodstream infection outcome using machine learning.

Proteogenomics of glioblastoma associates molecular patterns with survival

Oral microbiota signatures in post-traumatic stress disorder (PTSD) veterans

Population differences in antibody response to SARS‐CoV‐2 infection and BNT162b2 vaccination