Harnessing the power of resistant starch: a narrative review of its health impact and processing challenges

Starch is a primary energy storage for plants, making it an essential component of many plant-based foods consumed today. Resistant starch (RS) refers to those starch fractions that escape digestion in the small intestine and reach the colon where they are fermented by the microflora. RS has been repeatedly reported as having benefits on health, but ensuring that its content remains in food processing may be challenging. The present work focuses on the impact RS on health and explores the different processes that may influence its presence in foods, thus potentially interfering with these effects. Clinical evidence published from 2010 to 2023 and studying the effect of RS on health parameters in adult populations, were identified, using PUBMED/Medline and Cochrane databases. The search focused as well on observational studies related to the effect of food processes on RS content. While processes such as milling, fermentation, cooking and heating seem to have a deleterious influence on RS content, other processes, such as cooling, cooking time, storage time, or water content, may positively impact its presence. Regarding the influence on health parameters, there is a body of evidence suggesting an overall significant beneficial effect of RS, especially type 1 and 2, on several health parameters such as glycemic response, insulin resistance index, bowel function or inflammatory markers. Effects are more substantiated in individuals suffering from metabolic diseases. The effects of RS may however be exerted differently depending on the type. A better understanding of the influence of food processes on RS can guide the development of dietary intake recommendations and contribute to the development of food products rich in RS

Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features

Purpose: The purpose of this study is classifying multiple sclerosis (MS) patients in the four clinical forms as defined by the McDonald criteria using machine learning algorithms trained on clinical data combined with lesion loads and magnetic resonance metabolic features.Materials and Methods: Eighty-seven MS patients [12 Clinically Isolated Syndrome (CIS), 30 Relapse Remitting (RR), 17 Primary Progressive (PP), and 28 Secondary Progressive (SP)] and 18 healthy controls were included in this study. Longitudinal data available for each MS patient included clinical (e.g., age, disease duration, Expanded Disability Status Scale), conventional magnetic resonance imaging and spectroscopic imaging. We extract N-acetyl-aspartate (NAA), Choline (Cho), and Creatine (Cre) concentrations, and we compute three features for each spectroscopic grid by averaging metabolite ratios (NAA/Cho, NAA/Cre, Cho/Cre) over good quality voxels. We built linear mixed-effects models to test for statistically significant differences between MS forms. We test nine binary classification tasks on clinical data, lesion loads, and metabolic features, using a leave-one-patient-out cross-validation method based on 100 random patient-based bootstrap selections. We compute F1-scores and BAR values after tuning Linear Discriminant Analysis (LDA), Support Vector Machines with gaussian kernel (SVM-rbf), and Random Forests.Results: Statistically significant differences were found between the disease starting points of each MS form using four different response variables: Lesion Load, NAA/Cre, NAA/Cho, and Cho/Cre ratios. Training SVM-rbf on clinical and lesion loads yields F1-scores of 71–72% for CIS vs. RR and CIS vs. RR+SP, respectively. For RR vs. PP we obtained good classification results (maximum F1-score of 85%) after training LDA on clinical and metabolic features, while for RR vs. SP we obtained slightly higher classification results (maximum F1-score of 87%) after training LDA and SVM-rbf on clinical, lesion loads and metabolic features.Conclusions: Our results suggest that metabolic features are better at differentiating between relapsing-remitting and primary progressive forms, while lesion loads are better at differentiating between relapsing-remitting and secondary progressive forms. Therefore, combining clinical data with magnetic resonance lesion loads and metabolic features can improve the discrimination between relapsing-remitting and progressive forms

Podbat: A Novel Genomic Tool Reveals Swr1-Independent H2A.Z Incorporation at Gene Coding Sequences through Epigenetic Meta-Analysis

Epigenetic regulation consists of a multitude of different modifications that determine active and inactive states of chromatin. Conditions such as cell differentiation or exposure to environmental stress require concerted changes in gene expression. To interpret epigenomics data, a spectrum of different interconnected datasets is needed, ranging from the genome sequence and positions of histones, together with their modifications and variants, to the transcriptional output of genomic regions. Here we present a tool, Podbat (Positioning database and analysis tool), that incorporates data from various sources and allows detailed dissection of the entire range of chromatin modifications simultaneously. Podbat can be used to analyze, visualize, store and share epigenomics data. Among other functions, Podbat allows data-driven determination of genome regions of differential protein occupancy or RNA expression using Hidden Markov Models. Comparisons between datasets are facilitated to enable the study of the comprehensive chromatin modification system simultaneously, irrespective of data-generating technique. Any organism with a sequenced genome can be accommodated. We exemplify the power of Podbat by reanalyzing all to-date published genome-wide data for the histone variant H2A.Z in fission yeast together with other histone marks and also phenotypic response data from several sources. This meta-analysis led to the unexpected finding of H2A.Z incorporation in the coding regions of genes encoding proteins involved in the regulation of meiosis and genotoxic stress responses. This incorporation was partly independent of the H2A.Z-incorporating remodeller Swr1. We verified an Swr1-independent role for H2A.Z following genotoxic stress in vivo. Podbat is open source software freely downloadable from www.podbat.org, distributed under the GNU LGPL license. User manuals, test data and instructions are available at the website, as well as a repository for third party–developed plug-in modules. Podbat requires Java version 1.6 or higher

High-resolution analysis of multi-copy variant surface glycoprotein gene expression sites in African trypanosomes

BACKGROUND: African trypanosomes cause lethal diseases in humans and animals and escape host immune attack by switching the expression of Variant Surface Glycoprotein (VSG) genes. The expressed VSGs are located at the ends of telomeric, polycistronic transcription units known as VSG expression sites (VSG-ESs). Each cell has many VSG-ESs but only one is transcribed in bloodstream-form parasites and all of them are inactive upon transmission to the insect vector mid-gut; a subset of monocistronic metacyclic VSG-ESs are then activated in the insect salivary gland. Deep-sequence analyses have been informative but assigning sequences to individual VSG-ESs has been challenging because they each contain closely related expression-site associated genes, or ESAGs, thought to contribute to virulence. RESULTS: We utilised ART, an in silico short read simulator to demonstrate the feasibility of accurately aligning reads to VSG-ESs. Then, using high-resolution transcriptomes from isogenic bloodstream and insect-stage Lister 427 Trypanosoma brucei, we uncover increased abundance in the insect mid-gut stage of mRNAs from metacyclic VSG-ESs and of mRNAs from the unusual ESAG, ESAG10. Further, we show that the silencing associated with allelic exclusion involves repression focussed at the ends of the VSG-ESs. We also use the approach to report relative fitness costs following ESAG RNAi from a genome-scale screen. CONCLUSIONS: By assigning sequences to individual VSG-ESs we provide new insights into VSG-ES transcription control, allelic exclusion and impacts on fitness. Thus, deeper insights into the expression and function of regulated multi-gene families are more accessible than previously anticipated. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3154-8) contains supplementary material, which is available to authorized users

The FUN30 Chromatin Remodeler, Fft3, Protects Centromeric and Subtelomeric Domains from Euchromatin Formation

The chromosomes of eukaryotes are organized into structurally and functionally discrete domains. This implies the presence of insulator elements that separate adjacent domains, allowing them to maintain different chromatin structures. We show that the Fun30 chromatin remodeler, Fft3, is essential for maintaining a proper chromatin structure at centromeres and subtelomeres. Fft3 is localized to insulator elements and inhibits euchromatin assembly in silent chromatin domains. In its absence, euchromatic histone modifications and histone variants invade centromeres and subtelomeres, causing a mis-regulation of gene expression and severe chromosome segregation defects. Our data strongly suggest that Fft3 controls the identity of chromatin domains by protecting these regions from euchromatin assembly

Comparative Genomics Reveals Two Novel RNAi Factors in Trypanosoma brucei and Provides Insight into the Core Machinery

The introduction ten years ago of RNA interference (RNAi) as a tool for molecular exploration in Trypanosoma brucei has led to a surge in our understanding of the pathogenesis and biology of this human parasite. In particular, a genome-wide RNAi screen has recently been combined with next-generation Illumina sequencing to expose catalogues of genes associated with loss of fitness in distinct developmental stages. At present, this technology is restricted to RNAi-positive protozoan parasites, which excludes T. cruzi, Leishmania major, and Plasmodium falciparum. Therefore, elucidating the mechanism of RNAi and identifying the essential components of the pathway is fundamental for improving RNAi efficiency in T. brucei and for transferring the RNAi tool to RNAi-deficient pathogens. Here we used comparative genomics of RNAi-positive and -negative trypanosomatid protozoans to identify the repertoire of factors in T. brucei. In addition to the previously characterized Argonaute 1 (AGO1) protein and the cytoplasmic and nuclear Dicers, TbDCL1 and TbDCL2, respectively, we identified the RNA Interference Factors 4 and 5 (TbRIF4 and TbRIF5). TbRIF4 is a 3′-5′ exonuclease of the DnaQ superfamily and plays a critical role in the conversion of duplex siRNAs to the single-stranded form, thus generating a TbAGO1-siRNA complex required for target-specific cleavage. TbRIF5 is essential for cytoplasmic RNAi and appears to act as a TbDCL1 cofactor. The availability of the core RNAi machinery in T. brucei provides a platform to gain mechanistic insights in this ancient eukaryote and to identify the minimal set of components required to reconstitute RNAi in RNAi-deficient parasites

45S rDNA Regions Are Chromosome Fragile Sites Expressed as Gaps In Vitro on Metaphase Chromosomes of Root-Tip Meristematic Cells in Lolium spp

BACKGROUND: In humans, chromosome fragile sites are regions that are especially prone to forming non-staining gaps, constrictions or breaks in one or both of the chromatids on metaphase chromosomes either spontaneously or following partial inhibition of DNA synthesis and have been well identified. So far, no plant chromosome fragile sites similar to those in human chromosomes have been reported. METHODS AND RESULTS: During the course of cytological mapping of rDNA on ryegrass chromosomes, we found that the number of chromosomes plus chromosome fragments was often more than the expected 14 in most cells for Lolium perenne L. cv. Player by close cytological examination using a routine chromosome preparation procedure. Further fluorescent in situ hybridization (FISH) using 45S rDNA as a probe indicated that the root-tip cells having more than a 14-chromosome plus chromosome fragment count were a result of chromosome breakage or gap formation in vitro (referred to as chromosome lesions) at 45S rDNA sites, and 86% of the cells exhibited chromosome breaks or gaps and all occurred at the sites of 45S rDNA in Lolium perenne L. cv. Player, as well as in L. multiflorum Lam. cv. Top One. Chromatin depletion or decondensation occurred at various locations within the 45S rDNA regions, suggesting heterogeneity of lesions of 45S rDNA sites with respect to their position within the rDNA region. CONCLUSIONS: The chromosome lesions observed in this study are very similar cytologically to that of fragile sites observed in human chromosomes, and thus we conclude that the high frequency of chromosome lesions in vitro in Lolium species is the result of the expression of 45S rDNA fragile sites. Possible causes for the spontaneous expression of fragile sites and their potential biological significance are discussed

Basal Body Positioning Is Controlled by Flagellum Formation in Trypanosoma brucei

To perform their multiple functions, cilia and flagella are precisely positioned at the cell surface by mechanisms that remain poorly understood. The protist Trypanosoma brucei possesses a single flagellum that adheres to the cell body where a specific cytoskeletal structure is localised, the flagellum attachment zone (FAZ). Trypanosomes build a new flagellum whose distal tip is connected to the side of the old flagellum by a discrete structure, the flagella connector. During this process, the basal body of the new flagellum migrates towards the posterior end of the cell. We show that separate inhibition of flagellum assembly, base-to-tip motility or flagella connection leads to reduced basal body migration, demonstrating that the flagellum contributes to its own positioning. We propose a model where pressure applied by movements of the growing new flagellum on the flagella connector leads to a reacting force that in turn contributes to migration of the basal body at the proximal end of the flagellum

Patterns and Mechanisms of Ancestral Histone Protein Inheritance in Budding Yeast

Tracking of ancestral histone proteins over multiple generations of genome replication in yeast reveals that old histones move along genes from 3′ toward 5′ over time, and that maternal histones move up to around 400 bp during genomic replication