Effectively addressing complex proteomic search spaces with peptide spectrum matching.

SUMMARY: Protein identification by mass spectrometry is commonly accomplished using a peptide sequence matching search algorithm, whose sensitivity varies inversely with the size of the sequence database and the number of post-translational modifications considered. We present the Spectrum Identification Machine, a peptide sequence matching tool that capitalizes on the high-intensity b1-fragment ion of tandem mass spectra of peptides coupled in solution with phenylisotiocyanate to confidently sequence the first amino acid and ultimately reduce the search space. We demonstrate that in complex search spaces, a gain of some 120% in sensitivity can be achieved. AVAILABILITY: All data generated and the software are freely available for academic use at http://proteomics.fiocruz.br/software/sim. CONTACT: paulo@pcarvalho.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

HI-bone: a scoring system for identifying phenylisothiocyanate-derivatized peptides based on precursor mass and high intensity fragment ions.

Peptide sequence matching algorithms used for peptide identification by tandem mass spectrometry (MS/MS) enumerate theoretical peptides from the database, predict their fragment ions, and match them to the experimental MS/MS spectra. Here, we present an approach for scoring MS/MS identifications based on the high mass accuracy matching of precursor ions, the identification of a high intensity b1 fragment ion, and partial sequence tags from phenylthiocarbamoyl-derivatized peptides. This derivatization process boosts the b1 fragment ion signal, which turns it into a powerful feature for peptide identification. We demonstrate the effectiveness of our scoring system by implementing it on a computational tool called "HI-bone" and by identifying mass spectra of an Escherichia coli sample acquired on an Orbitrap Velos instrument using Higher-energy C-trap dissociation. Following this strategy, we identified 1614 peptide spectrum matches with a peptide false discovery rate (FDR) below 1%. These results were significantly higher than those from Mascot and SEQUEST using a similar FDR.

The Prevalence of COVID-19 Fog and the Impact on Quality of Life After SARS-CoV-2 Infection (QoL-COVID): A Cross Sectional Study.

INTRODUCTION: Coronavirus has an impact on both the physical and mental health of individuals. The literature regarding the patient's health status post-SARS-CoV-2 is still scarce with limited data on the prevalence of residual symptoms and quality of life (QoL) after the infection. The aim of this study was to understand the impact of SARS-CoV-2 on patient QoL, and remaining symptoms. MATERIAL AND METHODS: Single center cross-sectional study of patients who had been admitted to our COVID-19 ward between March 2020 and March 2021. By applying a QoL questionnaire (EQ-5D-5L) we assessed the overall sample, at three time points and in different groups of patients: those admitted to the intensive care unit (ICU) and the elderly. RESULTS: A total of 125 participants were included in our study. Most patients who were admitted had a severe course of disease (51%), with 22% of admissions to the ICU, with 8% requiring prone ventilation, 10% experiencing thrombotic complications and 18% of nosocomial infections throughout the admission. As for persistent symptoms related with COVID-19 fog, the most frequent were fatigue (57%), memory loss (52%) and insomnia (50%). Regarding QoL, the average decrease was 0.08 ± 0.2 in the index and 8.7 ± 19 in the Visual Analogue Scale (VAS). The QoL index decrease correlated with age, chronic obstructive pulmonary disease, asthma and heart failure, and all persistent symptoms, significantly. QoL VAS correlated significantly with fatigue, mood changes, difficulty concentrating and memory loss. The decrease in QoL and the persistent symptoms remained overall stable over the three time points. The ICU group showed no statistically significant difference in QoL, but the most frequently persistent symptoms were mood changes and attention disturbances. However, the elderly experienced a worsening in QoL expressed by index (0.69 ± 0.3 vs 0.8 ± 0.2, p-value = 0.01). CONCLUSION: A decrease in QoL was observed following SARS-CoV-2 infection, correlating with both chronic conditions and persistent symptoms. The lack of difference through time points of both QoL and persistent symptoms suggests a long-standing effect.

Telemedicine multimedia system to support neurodegenerative diseases participatory management.

Parkinson's disease (PD) is a highly prevalent and disabling condition that requires a constant monitoring of patient's condition. Nevertheless, in Portugal appointments with specialist only occur every 6 months and the patient's capability to recall important past events is not always accurate besides often being a misinterpretation of their symptoms. In this paper we present a user-centred process for the design of a multimedia platform for the self-management of PD.

Enhanced saccharification of sugarcane bagasse using soluble cellulase supplemented with immobilized ß-glucosidase.

The ß-glucosidase (BG) enzyme plays a vital role in the hydrolysis of lignocellulosic biomass. Supplementation of the hydrolysis reaction medium with BG can reduce inhibitory effects, leading to greater conversion. In addition, the inclusion of immobilized BG can be a useful way of increasing enzyme stability and recyclability. BG was adsorbed on polyacrylic resin activated by carboxyl groups (BG-PC) and covalently attached to glyoxyl-agarose (BG-GA). BG-PC exhibited similar behavior to soluble BG in the hydrolysis of cellobiose, while BG-GA hydrolyzed the same substrate at a lower rate. However, the thermal stability of BG-GA was higher than that of free BG. Hydrolysis of pretreated sugarcane bagasse catalyzed by soluble cellulase supplemented with immobilized BG improved the conversion by up to 40% after 96 h of reaction. Both derivatives remained stable up to the third cycle and losses of activity were less than 50% after five cycles.

Characterization of ß -Glucosidase Produced by Aspergillus niger under Solid-State Fermentation and Partially Purified Using MANAE-Agarose.

ß -Glucosidase (BGL) is a hydrolytic enzyme with specificity for a wide variety of glycoside substrates, being an enzyme with a large range of biotechnological applications. However, enzyme properties can be different depending both on the microorganism and the cultivation procedure employed. Therefore, in order to explore potential biocatalytical applications of novel enzymes, their characterization is essential. In this work, a BGL synthesized by a selected strain of Aspergillus niger cultivated under solid-state fermentation (SSF) was partially purified and fully characterized in terms of optimum pH, temperature, and thermostability. The single-step purification using MANAE-agarose in a chromatographic column yielded an enzyme solution with specific activity (17.1 IU/mg protein) adequate for the characterization procedures. Electrophoresis SDS-PAGE and size-exclusion chromatography analysis resulted in an estimated molecular mass of 60 kDa. Higher enzyme activities were found in the range between 40 and 65°C and between pH 4 and 5.5, indicating an interesting characteristic for application in the hydrolysis of lignocellulosic biomass for biofuels production. Thermostability studies of purified BGL resulted in half-lives at 37°C of 56.3 h and at 50°C of 5.4 h. These results provide support for further studies of this enzyme towards revealing its potential biotechnological applications.