An analysis of the Sargasso Sea resource and the consequences for database composition

Background: The environmental sequencing of the Sargasso Sea has introduced a huge new resource of genomic information. Unlike the protein sequences held in the current searchable databases, the Sargasso Sea sequences originate from a single marine environment and have been sequenced from species that are not easily obtainable by laboratory cultivation. The resource also contains very many fragments of whole protein sequences, a side effect of the shotgun sequencing method.These sequences form a significant addendum to the current searchable databases but also present us with some intrinsic difficulties. While it is important to know whether it is possible to assign function to these sequences with the current methods and whether they will increase our capacity to explore sequence space, it is also interesting to know how current bioinformatics techniques will deal with the new sequences in the resource.Results: The Sargasso Sea sequences seem to introduce a bias that decreases the potential of current methods to propose structure and function for new proteins. In particular the high proportion of sequence fragments in the resource seems to result in poor quality multiple alignments.Conclusion: These observations suggest that the new sequences should be used with care, especially if the information is to be used in large scale analyses. On a positive note, the results may just spark improvements in computational and experimental methods to take into account the fragments generated by environmental sequencing techniques

A database of immunoglobulins with integrated tools: DIGIT

The DIGIT (Database of ImmunoGlobulins with Integrated Tools) database (http://biocomputing.it/digit) is an integrated resource storing sequences of annotated immunoglobulin variable domains and enriched with tools for searching and analyzing them. The annotations in the database include information on the type of antigen, the respective germline sequences and on pairing information between light and heavy chains. Other annotations, such as the identification of the complementarity determining regions, assignment of their structural class and identification of mutations with respect to the germline, are computed on the fly and can also be obtained for user-submitted sequences. The system allows customized BLAST searches and automatic building of 3D models of the domains to be performed

Learning Linear Non-Gaussian Polytree Models

In the context of graphical causal discovery, we adapt the versatile framework of linear non-Gaussian acyclic models (LiNGAMs) to propose new algorithms to efficiently learn graphs that are polytrees. Our approach combines the Chow--Liu algorithm, which first learns the undirected tree structure, with novel schemes to orient the edges. The orientation schemes assess algebraic relations among moments of the data-generating distribution and are computationally inexpensive. We establish high-dimensional consistency results for our approach and compare different algorithmic versions in numerical experiments

LSD1: more than demethylation of histone lysine residues

Lysine-specific histone demethylase 1 (LSD1) represents the first example of an identified nuclear protein with histone demethylase activity. In particular, it plays a special role in the epigenetic regulation of gene expression, as it removes methyl groups from mono- and dimethylated lysine 4 and/or lysine 9 on histone H3 (H3K4me1/2 and H3K9me1/2), behaving as a repressor or activator of gene expression, respectively. Moreover, it has been recently found to demethylate monomethylated and dimethylated lysine 20 in histone H4 and to contribute to the balance of several other methylated lysine residues in histone H3 (i.e., H3K27, H3K36, and H3K79). Furthermore, in recent years, a plethora of nonhistone proteins have been detected as targets of LSD1 activity, suggesting that this demethylase is a fundamental player in the regulation of multiple pathways triggered in several cellular processes, including cancer progression. In this review, we analyze the molecular mechanism by which LSD1 displays its dual effect on gene expression (related to the specific lysine target), placing final emphasis on the use of pharmacological inhibitors of its activity in future clinical studies to fight cancer

Covalent Binding Antibodies Suppress Advanced Glycation: On the Innate Tier of Adaptive Immunity

Non-enzymatic protein glycation is a source of metabolic stress that contributes to cytotoxicity and tissue damage. Hyperglycemia has been linked to elevation of advanced glycation endproducts, which mediate much of the vascular pathology leading to diabetic complications. Enhanced glycation of immunoglobulins and their accelerated vascular clearance is proposed as a natural mechanism to intercept alternative advanced glycation endproducts, thereby mitigating microvascular disease. We reported that antibodies against the glycoprotein KLH have elevated reactivity for glycopeptides from diabetic serum. These reactions are mediated by covalent binding between antibody light chains and carbonyl groups of glycated peptides. Diabetic animals that were immunized to induce reactive antibodies had attenuated diabetic nephropathy, which correlated with reduced levels of circulating and kidney-bound glycation products. Molecular analysis of antibody glycation revealed the preferential modification of light chains bearing germline-encoded lambda V regions. We previously noted that antibody fragments carrying V regions in the germline configuration are selected from a human Fv library by covalent binding to a reactive organophosphorus ester. These Fv fragments were specifically modified at light chain V region residues, which map to the combining site at the interface between light and heavy chains. These findings suggest that covalent binding is an innate property of antibodies, which may be encoded in the genome for specific physiological purposes. This hypothesis is discussed in context with current knowledge of the natural antibodies that recognize altered self molecules and the catalytic autoantibodies found in autoimmune disease

Video Suppression Head Impulses and Head Impulses Paradigms in Patients with Vestibular Neuritis: A Comparative Study

Background: This study aims to explore the clinical relevance of the Suppression Head Impulse Paradigm (SHIMP) to better understand if it represents an additional clinical value compared to the Head Impulse Paradigm (HIMP) in patients with vestibular neuritis (VN) in different stages of the disease. Methods: From January 2020 to June 2022, patients with unilateral VN were found in a database of an ENT vestibular clinic. Clinical presentation, vestibular test outcomes, therapy, and recovery were examined in medical records. Results: A total of 42 patients (16 Females, mean age 51.06 ± 12.96; 26 Male, mean age 62.50 ± 9.82) met the inclusion criteria and were enrolled in the study. The means of the VOR gain for both paradigms were respectively 0.38 ± 0.12 (SHIMP) and 0.46 ± 0.13 (HIMP) at T0 and 0.55 ± 0.20 (SHIMP) and 0.64 ± 0.19 (HIMP) at T1 for the lesional side. For the HIMP, the gain value <0.76 identified the affected side of VN with 100% sensitivity (92–100) and 100% specificity (91–100). For the SHIMP, the gain value <0.66 identified the affected side of VN with 100% sensitivity (92–100) and 100% specificity (91–100) and an AUC of 1.0 (0.96–1.0, p < 0.0001). Conclusion: The SHIMP paradigm has a diagnostic accuracy equal to the classic HIMP paradigm in patients with VN. The assessment of VOR slow phase velocity and vestibulo-saccadic interaction in patients with VN could be easier with the use of the SHIMPs paradigm. SHIMPs paradigm provides helpful information about the evaluation of VOR slow phase velocity and vestibulo-saccadic interaction as new recovery strategies in patients with VN

Epigenome chaos: Stochastic and deterministic dna methylation events drive cancer evolution

Cancer evolution is associated with genomic instability and epigenetic alterations, which contribute to the inter and intra tumor heterogeneity, making genetic markers not accurate to monitor tumor evolution. Epigenetic changes, aberrant DNA methylation and modifications of chromatin proteins, determine the “epigenome chaos”, which means that the changes of epigenetic traits are randomly generated, but strongly selected by deterministic events. Disordered changes of DNA methylation profiles are the hallmarks of all cancer types, but it is not clear if aberrant methylation is the cause or the consequence of cancer evolution. Critical points to address are the profound epigenetic intra-and inter-tumor heterogeneity and the nature of the heterogeneity of the methylation patterns in each single cell in the tumor population. To analyze the methylation heterogeneity of tumors, new technological and informatic tools have been developed. This review discusses the state of the art of DNA methylation analysis and new approaches to reduce or solve the complexity of methylated alleles in DNA or cell populations