Application of the broadband collision-induced dissociation (bbCID) mass spectrometry approach for protein glycosylation and phosphorylation analysis

Rationale Analysis of post‐translationally modified peptides by mass spectrometry (MS) remains incomplete, in part due to incomplete sampling of all peptides which is inherent to traditional data‐dependent acquisition (DDA). An alternative MS approach, data‐independent acquisition (DIA), enables comprehensive recording of all detectable precursor and product ions, independent of precursor intensity. The use of broadband collision‐induced dissociation (bbCID), a DIA method, was evaluated for the identification of protein glycosylation and phosphorylation. Methods bbCID was applied to identify glycopeptides and phosphopeptides generated from standard proteins using a high‐resolution Bruker maXis 3G mass spectrometer. In bbCID, precursor and product ion spectra were obtained by alternating low and high collision energy. Precursor ions were assigned manually based on the detection of diagnostic ions specific to either glycosylation or phosphorylation. The composition of the glycan modification was resolved in the positive ion mode, while the level of phosphorylation was investigated in the negative ion mode. Results The results demonstrate for the first time that the use of a bbCID approach is suitable for the identification of glycopeptides and phosphopeptides based on the detection of specific diagnostic and associated precursor ions. The novel use of bbCID in negative ion mode allowed the discrimination of singly and multiply phosphorylated peptides based on the detection of phosphate diagnostic ions. The results also demonstrate the ability of this approach to allow the identification of glycan composition in N‐ and O‐linked glycopeptides, in positive ion mode. Conclusions We contend that bbCID is a valuable addition to the existing toolkit for PTM discovery. Moreover, this technique could be employed to direct targeted proteomics methods, particularly where there is no a priori information on glycosylation or phosphorylation status. This technique is immediately relevant to the characterisation of individual proteins or biological samples of low complexity, as demonstrated for the analysis of the glycosylation status of a therapeutic protein

Deciphering the unique cellulose degradation mechanism of the ruminal bacterium Fibrobacter succinogenes S85

Fibrobacter succinogenes S85, isolated from the rumen of herbivores, is capable of robust lignocellulose degradation. However, the mechanism by which it achieves this is not fully elucidated. In this study, we have undertaken the most comprehensive quantitative proteomic analysis, to date, of the changes in the cell envelope protein profile of F. succinogenes S85 in response to growth on cellulose. Our results indicate that the cell envelope proteome undergoes extensive rearrangements to accommodate the cellulolytic degradation machinery, as well as associated proteins involved in adhesion to cellulose and transport and metabolism of cellulolytic products. Molecular features of the lignocellulolytic enzymes suggest that the Type IX secretion system is involved in the translocation of these enzymes to the cell envelope. Finally, we demonstrate, for the first time, that cyclic-di-GMP may play a role in mediating catabolite repression, thereby facilitating the expression of proteins involved in the adhesion to lignocellulose and subsequent lignocellulose degradation and utilisation. Understanding the fundamental aspects of lignocellulose degradation in F. succinogenes will aid the development of advanced lignocellulosic biofuels

Quantitative proteomic comparison of salt stress in Chlamydomonas reinhardtii and the snow alga Chlamydomonas nivalis reveals mechanisms for salt-triggered fatty acid accumulation via reallocation of carbon resources

Background Chlamydomonas reinhardtii is a model green alga strain for molecular studies; its fully sequenced genome has enabled omic-based analyses that have been applied to better understand its metabolic responses to stress. Here, we characterised physiological and proteomic changes between a low-starch C. reinhardtii strain and the snow alga Chlamydomonas nivalis, to reveal insights into their contrasting responses to salinity stress. Results Each strain was grown in conditions tailored to their growth requirements to encourage maximal fatty acid (as a proxy measure of lipid) production, with internal controls to allow comparison points. In 0.2 M NaCl, C. nivalis accumulates carbohydrates up to 10.4% DCW at 80 h, and fatty acids up to 52.0% dry cell weight (DCW) over 12 days, however, C. reinhardtii does not show fatty acid accumulation over time, and shows limited carbohydrate accumulation up to 5.5% DCW. Analysis of the C. nivalis fatty acid profiles showed that salt stress improved the biofuel qualities over time. Photosynthesis and respiration rates are reduced in C. reinhardtii relative to C. nivalis in response to 0.2 M NaCl. De novo sequencing and homology matching was used in conjunction with iTRAQ-based quantitative analysis to identify and relatively quantify proteomic alterations in cells exposed to salt stress. There were abundance differences in proteins associated with stress, photosynthesis, carbohydrate and lipid metabolism proteins. In terms of lipid synthesis, salt stress induced an increase in dihydrolipoyl dehydrogenase in C. nivalis (1.1-fold change), whilst levels in C. reinhardtii remained unaffected; this enzyme is involved in acetyl CoA production and has been linked to TAG accumulation in microalgae. In salt-stressed C. nivalis there were decreases in the abundance of UDP-sulfoquinovose (− 1.77-fold change), which is involved in sulfoquinovosyl diacylglycerol metabolism, and in citrate synthase (− 2.7-fold change), also involved in the TCA cycle. Decreases in these enzymes have been shown to lead to increased TAG production as fatty acid biosynthesis is favoured. Data are available via ProteomeXchange with identifier PXD018148. Conclusions These differences in protein abundance have given greater understanding of the mechanism by which salt stress promotes fatty acid accumulation in the un-sequenced microalga C. nivalis as it switches to a non-growth state, whereas C. reinhardtii does not have this response

The alternative sigma factor SigF is a key player in the control of secretion mechanisms in Synechocystis sp. PCC 6803.

Cyanobacterial alternative sigma factors are crucial players in environmental adaptation processes, which may involve bacterial responses related to maintenance of cell envelope and control of secretion pathways. Here, we show that the Group 3 alternative sigma factor F (SigF) plays a pleiotropic role in Synechocystis sp. PCC 6803 physiology, with a major impact on growth and secretion mechanisms, such as the production of extracellular polysaccharides, vesiculation and protein secretion. Although ΔsigF growth was significantly impaired, the production of released polysaccharides (RPS) increased 3 to 4-fold compared to the wild-type. ΔsigF exhibits also impairment in formation of outer-membrane vesicles (OMVs) and pili, as well as several other cell envelope alterations. Similarly, the exoproteome composition of ΔsigF differs from the wild-type both in amount and type of proteins identified. Quantitative proteomics (iTRAQ) and an in silico analysis of SigF binding motifs revealed possible targets/pathways under SigF control. Besides changes in protein levels involved in secretion mechanisms, our results indicated that photosynthesis, central carbon metabolism, and protein folding/degradation mechanisms are altered in ΔsigF. Overall, this work provided new evidences about the role of SigF on Synechocystis physiology and associates this regulatory element with classical and non-classical secretion pathways

Exatidão dos dados do sistema de vigilância epidemiológica da malária no estado do Amazonas

The Epidemiological Surveillance System for Malaria (SIVEP-Malaria) is the Brazilian governmental program that registers all information about compulsory reporting of detected cases of malaria by all medical units and medical practitioners. The objective of this study is to point out the main sources of errors in the SIVEP-Malaria database by applying a data cleaning method to assist researchers about the best way to use it and to report the problems to authorities. The aim of this study was to assess the quality of the data collected by the surveillance system and its accuracy. The SIVEP-Malaria data base used was for the state of Amazonas, Brazil, with data collected from 2003 to 2014. A data cleaning method was applied to the database to detect and remove erroneous records. It was observed that the collecting procedure of the database is not homogeneous among the municipalities and over the years. Some of the variables had different data collection periods, missing data, outliers and inconsistencies. Variables depending on the health agents showed a good quality but those that rely on patients were often inaccurate. We showed that a punctilious preprocessing is needed to produce statistically correct data from the SIVEP-Malaria data base. Fine spatial scale and multi-temporal analysis are of particular concern due to the local concentration of uncertainties and the data collecting seasonality observed. This assessment should help to enhance the quality of studies and the monitoring of the use of the SIVEP database.O Sistema de Vigilância Epidemiológica de Malária (SIVEP-Malária) é um programa governamental brasileiro que arquiva automaticamente todas as informações sobre casos de malária registrados em todas as unidades de saúde e consultórios medicos. O objetivo deste estudo foi avaliar a qualidade dos dados coletados pelo sistema de vigilância e sua precisão. Foram utilizados os dados do SIVEP-Malária para o estado do Amazonas, Brasil, de 2003 a 2014. Um método de limpeza de dados foi aplicado para detectar e remover registros errôneos. Observamos que a coleta de dados não é homogênea entre os municipios e ao longo dos anos. Algumas variaveis tinham diferentes padrões de coleta, falta de dados, dados discrepantes e inconsistências. Dados que dependem do agente de saúde possuem boa qualidade mas aqueles que dependem dos pacientes são frequentemente imprecisos. Mostramos que um pre-processamento meticuloso é necessário para produzir dados estatisticamente corretos a partir do SIVEP-Malária. Analises em escala espacial detalhada ou multi-temporais são particularmente afetadas devido à concentração local de incertezas e a sazonalidade observada na coleta de dados. Esta avaliação deve auxiliar a melhorar os estudos e monitoramentos que fazem uso dos dados do SIVEP