The mRNA-binding proteome of a critical phase transition during Arabidopsis seed germination

International audienceArabidopsis thaliana seed germination is marked by extensive translational control at two critical phase transitions. The first transition refers to the start of hydration, the hydration translational shift. The second shift, the germination translational shift (GTS) is the phase between testa rupture and radicle protrusion at which the seed makes the all or nothing decision to germinate.The mechanism behind the translational regulation at these phase transitions is unknown. RNA binding proteins are versatile players in the post-transcriptional control of mRNAs and as such candidates for regulating translation during seed germination.Here, we report the mRNA binding protein repertoire of seeds during the GTS. Thirty seed specific RBPs and 22 dynamic RBPs were identified during the GTS, like the putative RBP Vacuolar ATPase subunit A and RBP HSP101. Several stress granule markers were identified in this study, which suggests that seeds are prepared to quickly adapt the translation of specific mRNAs in response to changes in environmental conditions during the GTS.Taken together this study provides a detailed insight into the world of RNA binding proteins during seed germination and their possible regulatory role during this developmentally regulated proces

Delayed Protein Changes During Seed Germination

Over the past decade, ample transcriptome data have been generated at different stages during seed germination; however, far less is known about protein synthesis during this important physiological process. Generally, the correlation between transcript levels and protein abundance is low, which strongly limits the use of transcriptome data to accurately estimate protein expression. Polysomal profiling has emerged as a tool to identify mRNAs that are actively translated. The association of the mRNA to the polysome, also referred to as translatome, provides a proxy for mRNA translation. In this study, the correlation between the changes in total mRNA, polysome-associated mRNA, and protein levels across seed germination was investigated. The direct correlation between polysomal mRNA and protein abundance at a single time-point during seed germination is low. However, once the polysomal mRNA of a time-point is compared to the proteome of the next time-point, the correlation is much higher. 35% of the investigated proteome has delayed changes at the protein level. Genes have been classified based on their delayed protein changes, and specific motifs in these genes have been identified. Moreover, mRNA and protein stability and mRNA length have been found as important predictors for changes in protein abundance. In conclusion, polysome association and/or dissociation predicts future changes in protein abundance in germinating seeds

Clostridium perfringens suppressing activity in black soldier fly protein preparations

Clostridium perfringens is a commensal, but also an opportunistic pathogen that can lead to lethal diseases as a result of overgrowth when homeostasis is disrupted. The current course of treatment is antibiotics. However, with increasing antibiotic resistance alternatives are required. We investigated the antimicrobial capacity of digest from different black soldier fly- and mealworm-derived fractions towards C. perfringens by using in vitro models. Culturing C. perfringens with digest of insect-derived fractions showed that fractions containing black soldier fly larvae protein significantly (p < 0.05) inhibited the growth of C. perfringens. In relation to this effect, many small (<5 amino acids) anti-microbial peptides were identified. The impact on healthy microbiota was also investigated through 16S rRNA sequencing and SCFA secretion following exposure of healthy faecal-derived microbiota to digests. This revealed a small but significant (p < 0.05) reduction in abundance and diversity of microbiota, mainly a result of a strong reduction in Firmicutes (e.g. Enterobacter) and increased abundance of Proteobacteria (e.g. Klebsiella). These changes coincided with increased levels of acetic, propionic, and butyric acid secretion. The combined impact of black soldier fly larvae protein on these in vitro assays suggest it can be a promising additional tool to combat C. perfringens infection

Improving the identification rate of data independent label-free quantitative proteomics experiments on non-model crops: A case study on apple fruit

Complex peptide extracts from non-model crops are troublesome for proper identification and quantification. To increase the identification rate of label free DIA experiments of Braeburn apple a new workflow was developed where a DDA database was constructed and linked to the DIA data. At a first level, parent masses found in DIA were searched in the DDA database based on their mass to charge ratio and retention time; at a second level, masses of fragmentation ions were compared for each of the linked spectrum. Following this workflow, a tenfold increase of peptides was identified from a single DIA run. As proof of principle, the designed workflow was applied to determine the changes during a storage experiment, achieving a two-fold identification increase in the number of significant peptides. The corresponding protein families were divided into nine clusters, representing different time profiles of changes in abundances during storage. Up-regulated protein families already show a glimpse of important pathways affecting aging during long-term storage, such as ethylene synthesis, and responses to abiotic stresses and their influence on the central metabolism. Biological significance: Proteomics research on non-model crops causes additional difficulties in identifying the peptides present in, often complex, samples. This work proposes a new workflow to retrieve more identifications from a set of quantitative data, based on linking DIA and DDA data at two consecutive levels. As proof of principle, a storage experiment on Braeburn apple resulted in twice as much identified storage related peptides. Important proteins involved in central metabolism and stress are significantly up-regulated after long term storage. This article is part of a Special Issue entitled: Proteomics of non-model organisms.</p

A combined microphysiological-computational omics approach in dietary protein evaluation

Food security is under increased pressure due to the ever-growing world population. To tackle this, alternative protein sources need to be evaluated for nutritional value, which requires information on digesta peptide composition in comparison to established protein sources and coupling to biological parameters. Here, a combined experimental and computational approach is presented, which compared seventeen protein sources with cow’s whey protein concentrate (WPC) as the benchmark. In vitro digestion of proteins was followed by proteomics analysis and statistical model-based clustering. Information on digesta peptide composition resulted in 3 cluster groups, primarily driven by the peptide overlap with the benchmark protein WPC. Functional protein data was then incorporated in the computational model after evaluating the effects of eighteen protein digests on intestinal barrier integrity, viability, brush border enzyme activity, and immune parameters using a bioengineered intestine as microphysiological gut system. This resulted in 6 cluster groups. Biological clustering was driven by viability, brush border enzyme activity, and significant differences in immune parameters. Finally, a combination of proteomic and biological efficacy data resulted in 5 clusters groups, driven by a combination of digesta peptide composition and biological effects. The key finding of our holistic approach is that protein source (animal, plant or alternative derived) is not a driving force behind the delivery of bioactive peptides and their biological efficacy

A combined microphysiological-computational omics approach in dietary protein evaluation

Food security is under increased pressure due to the ever-growing world population. To tackle this, alternative protein sources need to be evaluated for nutritional value, which requires information on digesta peptide composition in comparison to established protein sources and coupling to biological parameters. Here, a combined experimental and computational approach is presented, which compared seventeen protein sources with cow’s whey protein concentrate (WPC) as the benchmark. In vitro digestion of proteins was followed by proteomics analysis and statistical model-based clustering. Information on digesta peptide composition resulted in 3 cluster groups, primarily driven by the peptide overlap with the benchmark protein WPC. Functional protein data was then incorporated in the computational model after evaluating the effects of eighteen protein digests on intestinal barrier integrity, viability, brush border enzyme activity, and immune parameters using a bioengineered intestine as microphysiological gut system. This resulted in 6 cluster groups. Biological clustering was driven by viability, brush border enzyme activity, and significant differences in immune parameters. Finally, a combination of proteomic and biological efficacy data resulted in 5 clusters groups, driven by a combination of digesta peptide composition and biological effects. The key finding of our holistic approach is that protein source (animal, plant or alternative derived) is not a driving force behind the delivery of bioactive peptides and their biological efficacy