Satellite DNA are long tandemly repeating sequences in a genome and may be organized as high-order repeats (HORs). They are enriched in centromeres and are challenging to assemble. Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs. Here we describe Satellite Repeat Finder (SRF), a new algorithm for reconstructing satellite repeat units and HORs from accurate reads or assemblies without prior knowledge on repeat structures. Applying SRF to real sequence data, we show that SRF could reconstruct known satellites in human and well-studied model organisms. We also find satellite repeats are pervasive in various other species, accounting for up to 12% of their genome contents but are often underrepresented in assemblies. With the rapid progress in genome sequencing, SRF will help the annotation of new genomes and the study of satellite DNA evolution even if such repeats are not fully assembled.

Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the essential roles of glycans. Still, it remains challenging to properly analyze large glycomics datasets, since the abundance of each glycan is dependent on many other glycans that share many intermediate biosynthetic steps. Furthermore, the overlap of measured glycans can be low across samples. We address these challenges with GlyCompare, a glycomic data analysis approach that accounts for shared biosynthetic steps for all measured glycans to correct for sparsity and non-independence in glycomics, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we study diverse N-glycan profiles from glycoengineered erythropoietin. We obtain biologically meaningful clustering of mutant cell glycoprofiles and identify knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyze human milk oligosaccharide profiles and find mother’s fucosyltransferase-dependent secretor-status indirectly impact the sialylation. Finally, we apply our method on mucin-type O-glycans, gangliosides, and site-specific compositional glycosylation data to reveal tissues and disease-specific glycan presentations. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data.

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro , bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility. Graphical Diagram of hypothesis for bacterial mediation of SARS-CoV-2 infection through heparan sulfate (HS).: It is well known that host microbes groom the mucosa where they reside. Recent investigations have shown that HS, a major component of mucosal layers, is necessary for SARS-CoV-2 infection. In this study we examine the impact of microbial modification of HS on viral attachment.

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.

The gastrointestinal (GI) tract is a site of replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and GI symptoms are often reported by patients. SARS-CoV-2 cell entry depends upon heparan sulfate (HS) proteoglycans, which commensal bacteria that bathe the human mucosa are known to modify. To explore human gut HS-modifying bacterial abundances and how their presence may impact SARS-CoV-2 infection, we developed a task-based analysis of proteoglycan degradation on large-scale shotgun metagenomic data. We observed that gut bacteria with high predicted catabolic capacity for HS differ by age and sex, factors associated with coronavirus disease 2019 (COVID-19) severity, and directly by disease severity during/after infection, but do not vary between subjects with COVID-19 comorbidities or by diet. Gut commensal bacterial HS-modifying enzymes reduce spike protein binding and infection of authentic SARS-CoV-2, suggesting that bacterial grooming of the GI mucosa may impact viral susceptibility. IMPORTANCE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019, can infect the gastrointestinal (GI) tract, and individuals who exhibit GI symptoms often have more severe disease. The GI tract’s glycocalyx, a component of the mucosa covering the large intestine, plays a key role in viral entry by binding SARS-CoV-2’s spike protein via heparan sulfate (HS). Here, using metabolic task analysis of multiple large microbiome sequencing data sets of the human gut microbiome, we identify a key commensal human intestinal bacteria capable of grooming glycocalyx HS and modulating SARS-CoV-2 infectivity in vitro . Moreover, we engineered the common probiotic Escherichia coli Nissle 1917 (EcN) to effectively block SARS-CoV-2 binding and infection of human cell cultures. Understanding these microbial interactions could lead to better risk assessments and novel therapies targeting viral entry mechanisms.