Co- and post-translational translocation through the protein-conducting channel:analogous mechanisms at work?

Many proteins are translocated across, or integrated into, membranes. Both functions are fulfilled by the 'translocon/translocase', which contains a membrane-embedded proteinconducting channel (PCC) and associated soluble factors that drive translocation and insertion reactions using nucleotide triphosphates as fuel. This perspective focuses on reinterpreting existing experimental data in light of a recently proposed PCC model comprising a front-to-front dimer of SecY or Sec61 heterotrimeric complexes. In this new framework, we propose (i) a revised model for SRP-SR-mediated docking of the ribosome-nascent polypeptide to the PCC; (ii) that the dynamic interplay between protein substrate, soluble factors and PCC controls the opening and closing of a transmembrane channel across, and/or a lateral gate into, the membrane; and (iii) that co-and post-translational translocation, involving the ribosome and SecA, respectively, not only converge at the PCC but also use analogous mechanisms for coordinating protein translocation

Food Security Characteristics Vary for Undergraduate and Graduate Students at a Midwest University

The study objective was to determine prevalence of food insecurity and its associations with socioecological model (SEM) characteristics for undergraduate and graduate students. An online questionnaire was distributed to a convenience sample of students aged 18–34 at a Midwestern university. Of the 938 responses, 675 were complete for analysis. Outcome measures included demographics, food security level, housing, food access barriers, coping strategies, and food assistance program usage. Results found that predictors associated with undergraduate food insecurity included non-White race, receipt of financial aid, lower self-reported health status, living off-campus, employment, and food cost (p < 0.001). Graduate student food insecurity was associated with Asian self-identification, employment, food cost, no time to prepare foods, and lack of foods for dietary needs (p < 0.001). Students with food insecurity were more likely to buy cheap food (p < 0.001). Almost 50% of food-insecure undergraduates asked friends or family to help buy food. Food-insecure students were more likely to want information on meal preparation and budgeting. More graduate students were likely to know of and use food pantries. Overall, food insecurity was higher among undergraduate than graduate students. Universities should consider institutional and policy changes tailored to the separate populations to mitigate the prevalence of campus food insecurity

Black Bean Pasta Meals with Varying Protein Concentrations Reduce Postprandial Glycemia and Insulinemia Similarly Compared to White Bread Control in Adults

Postprandial glycemic and insulinemic effects of three black bean pastas were evaluated among eighteen normoglycemic adults (8 men, 10 women) in a randomized crossover trial. Black beans were milled into flour using a commercial Knife or compression/decompression mill (C/D mill). The C/D-mill-derived pastas had medium protein (Combo-MP) and low protein (Cyclone-LP) concentrations. Three black bean flour pastas (Knife, Combo-MP, and Cyclone-LP) were compared to two controls: white bread and whole black beans. Treatments contained 50 g of available carbohydrate. Plasma glucose, serum insulin, and appetite measures were collected at fasting and 30, 60, 90, 150, and 180 min postprandial. Gastrointestinal symptoms were evaluated 10-12 h postprandial. ANOVA (one-way, repeated measures) was used to evaluate satiety, gastrointestinal symptoms, sensory variables, glucose and insulin differences from baseline, and incremental area under the curve (iAUC) by time and/or treatment. Three-hour glucose and insulin iAUCs were lower with whole black beans than white bread. Black bean pasta meals increased satiety, reduced appetite, and produced numerically lower glucose and insulin responses than white bread. However, no differences were observed between pasta types, indicating a similar metabolic response regardless of milling technique. Our results provide evidence for dietary guidance to reduce postprandial glucose and related health risks through pulse food products.This article is published as Winham DM, Thompson SV, Heer MM, Davitt ED, Hooper SD, Cichy KA, Knoblauch ST. Black Bean Pasta Meals with Varying Protein Concentrations Reduce Postprandial Glycemia and Insulinemia Similarly Compared to White Bread Control in Adults. Foods. 2022 Jun 3;11(11):1652. doi: 10.3390/foods11111652. Posted with permission

Detection of PDI in <i>V</i>. <i>cholera</i>.

<p>A-D. Analysis of PDI by 5′ RNA-seq. Percentage of transcripts emanating from position −1 of uTSRs (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s003" target="_blank">S2</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s004" target="_blank">S3</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s005" target="_blank">S4</a> Tables) with the indicated sequence at −1 and +1 in cells carrying wild-type concentrations of 2- to ~4-nt RNAs (wild-type) or cells in which the oligoRNase NrnB was ectopically expressed (Nrn). The Nrn effect reported in panels A and C represents the difference in these values. uTSRs with above average Nrn effect are highlighted in black. The total number of uTSRs used to calculate the percentages is indicated. Values in panels A and B are calculated from biological replicates listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s003" target="_blank">S2 Table</a>, values in panel C is calculated from replicates listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s004" target="_blank">S3 Table</a> and values in panel D are calculated from replicates listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s005" target="_blank">S4 Table</a>. exp, exponential phase; sta, stationary phase; all, analysis of all 5′ ends; ppp, analysis of 5′ triphosphate ends; ppp+OH, analysis of 5′ triphosphate ends and 5′ hydroxyl ends; ppp+p, analysis of 5′ triphosphate ends and 5′ monophosphate ends. E. and F. Analysis of PDI at the promoters associated with <i>VC1904</i> (pVC1904) and <i>VCA0783</i> (p<i>VCA0783</i>). Top of each panel shows promoter sequence. Indicated are positions +1, −1 and the promoter −10 and −35 elements. Middle of each panel shows results of 5′ RNA-seq. Graphs on left show average distribution of all 5′ ends between positions −3 and +4 in cells carrying wild-type concentrations of 2- to ~4-nt RNAs (wt) or cells in which the oligoRNase NrnB was ectopically expressed (Nrn) as detected by 5′ RNA-seq during stationary phase. Graphs on the right show average distribution of all 5′ ends between positions −3 and +4 for p<i>VCA0783</i> in wild-type cells during stationary phase (sta) or exponential phase (exp). Bottom of each panel shows primer extension analysis of plasmid-borne promoter variants carrying the indicated sequences at positions −1/+1 (left) or primer extension analysis of chromosomally encoded promoters during exponential phase (exp) or stationary phase (sta).</p

Detection of PDI in <i>E</i>. <i>coli</i>.

<p>A. Analysis of PDI by 5′ RNA-seq. Percentage of transcripts emanating from position −1 of uTSRs with the indicated sequence at −1 and +1 in cells carrying wild-type concentrations of 2- to ~4-nt RNAs (wild-type) or cells in which the oligoRNase NrnB was ectopically expressed (Nrn). The Nrn effect represents the difference in these values. uTSRs with above average Nrn effect are highlighted in black. The total number of uTSRs used to calculate the percentages is indicated. Values are calculated from biological replicates listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005348#pgen.1005348.s009" target="_blank">S8 Table</a>. Data is derived from the analysis of all 5′ ends during stationary phase. B. Analysis of PDI at the promoter associated with <i>tomB</i>, p<i>tomB</i>, by 5′ RNA-seq. Sequence of p<i>tomB</i> is shown. Indicated are positions +1, −1 and the promoter −10 and −35 elements. Graph on the left shows average distribution of 5′ ends between positions −3 and +4 for p<i>tomB</i> in cells carrying wild-type concentrations of 2- to ~4-nt RNAs or cells in which the oligoRNase NrnB was ectopically expressed (Nrn) as detected by 5′ RNA-seq analysis of all 5′ ends during stationary phase. Graph on the right shows the average distribution of 5′ ends between positions −3 and +4 for p<i>tomB</i> in cells carrying wild-type concentrations of 2- to ~4-nt RNAs as detected by 5′ RNA-seq analysis of hydroxyl 5′ ends (OH), monophosphate 5′ ends (P), or triphosphate 5′ ends (PPP) during stationary phase. C. Primer extension analysis of plasmid-borne p<i>tomB</i> variants carrying the indicated sequence at −1 and +1 in cells carrying wild-type concentrations of 2- to ~4-nt RNAs (wt) or cells in which the oligoRNase NrnB was ectopically expressed (Nrn). D. Primer extension analysis of the plasmid-borne p<i>tomB</i> variant carrying the sequence G₋₁G₊₁ during exponential phase (exp) or stationary phase (sta).</p

From Harare to Rio de Janeiro : Kukiya-Favela organization of the excluded

This article, based on ethnographic research conducted with people in Brazil and Zimbabwe, reports organization/management experiences and narratives of poor and marginalized people of the south. South embodies the organizational struggle, survival skills and resilience of marginal and urban outcasts that inhabit inner cities, townships and slums. The article employs the notion of kukiya-favela organization, i.e. the organization of the excluded, to engage with them in order to: give voice to those who dwell at the margins of organization studies; make their narratives part of a subject that retains an elitist position; and re-address the Eurocentric management/organization discourse that imposes a legitimate justification for exploiting, excluding and labelling them as organization-less and urban outcasts of society. The article concludes that despite their marginality and exclusion they are able to construct local diverse meaningful (organizational) identities that can represent them with dignity in their struggle for justice and basic human rights. Finally, it reflects on the contribution this has for us, in organization studies, by opening new spaces for the study of organization[al] (lives) not from positions of ‘above’ or ‘against’ but ‘with’ (Gergen, 2003: 454)

The Hitchhiker’s Guide to Statistical Analysis of Feature-based Molecular Networks from Non-Targeted Metabolomics Data

Feature-Based Molecular Networking (FBMN) is a popular analysis approach for LC-MS/MS-based non-targeted metabolomics data. While processing LC-MS/MS data through FBMN is fairly streamlined, downstream data handling and statistical interrogation is often a key bottleneck. Especially, users new to statistical analysis struggle to effectively handle and analyze complex data matrices. In this protocol, we provide a comprehensive guide for the statistical analysis of FBMN results. We explain the data structure and principles of data clean-up and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. Additionally, the protocol is accompanied by a web application with a graphical user interface (https://fbmn-statsguide.gnps2.org/), to lower the barrier of entry for new users. Together, the protocol, code, and web app provide a complete guide and toolbox for FBMN data integration, clean-up, and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking (GNPS and GNPS2) and can be adapted to other MS feature detection, annotation, and networking tools