Bacterial riboproteogenomics : the era of N-terminal proteoform existence revealed

With the rapid increase in the number of sequenced prokaryotic genomes, relying on automated gene annotation became a necessity. Multiple lines of evidence, however, suggest that current bacterial genome annotations may contain inconsistencies and are incomplete, even for so-called well-annotated genomes. We here discuss underexplored sources of protein diversity and new methodologies for high-throughput genome re-annotation. The expression of multiple molecular forms of proteins (proteoforms) from a single gene, particularly driven by alternative translation initiation, is gaining interest as a prominent contributor to bacterial protein diversity. In consequence, riboproteogenomic pipelines were proposed to comprehensively capture proteoform expression in prokaryotes by the complementary use of (positional) proteomics and the direct readout of translated genomic regions using ribosome profiling. To complement these discoveries, tailored strategies are required for the functional characterization of newly discovered bacterial proteoforms

Overexpression of a Prefoldin β subunit gene reduces biomass recalcitrance in the bioenergy crop Populus.

Prefoldin (PFD) is a group II chaperonin that is ubiquitously present in the eukaryotic kingdom. Six subunits (PFD1-6) form a jellyfish-like heterohexameric PFD complex and function in protein folding and cytoskeleton organization. However, little is known about its function in plant cell wall-related processes. Here, we report the functional characterization of a PFD gene from Populus deltoides, designated as PdPFD2.2. There are two copies of PFD2 in Populus, and PdPFD2.2 was ubiquitously expressed with high transcript abundance in the cambial region. PdPFD2.2 can physically interact with DELLA protein RGA1_8g, and its subcellular localization is affected by the interaction. In P. deltoides transgenic plants overexpressing PdPFD2.2, the lignin syringyl/guaiacyl ratio was increased, but cellulose content and crystallinity index were unchanged. In addition, the total released sugar (glucose and xylose) amounts were increased by 7.6% and 6.1%, respectively, in two transgenic lines. Transcriptomic and metabolomic analyses revealed that secondary metabolic pathways, including lignin and flavonoid biosynthesis, were affected by overexpressing PdPFD2.2. A total of eight hub transcription factors (TFs) were identified based on TF binding sites of differentially expressed genes in Populus transgenic plants overexpressing PdPFD2.2. In addition, several known cell wall-related TFs, such as MYB3, MYB4, MYB7, TT8 and XND1, were affected by overexpression of PdPFD2.2. These results suggest that overexpression of PdPFD2.2 can reduce biomass recalcitrance and PdPFD2.2 is a promising target for genetic engineering to improve feedstock characteristics to enhance biofuel conversion and reduce the cost of lignocellulosic biofuel production

Protein (Multi-)Location Prediction: Using Location Inter-Dependencies in a Probabilistic Framework

Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins, assuming that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems have attempted to predict multiple locations of proteins, they typically treat locations as independent or capture inter-dependencies by treating each locations-combination present in the training set as an individual location-class. We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the multiple-location-prediction process, using a collection of Bayesian network classifiers. We evaluate our system on a dataset of single- and multi-localized proteins. Our results, obtained by incorporating inter-dependencies are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without restricting predictions to be based only on location-combinations present in the training set.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Fundamental Limits to Position Determination by Concentration Gradients

Position determination in biological systems is often achieved through protein concentration gradients. Measuring the local concentration of such a protein with a spatially-varying distribution allows the measurement of position within the system. In order for these systems to work effectively, position determination must be robust to noise. Here, we calculate fundamental limits to the precision of position determination by concentration gradients due to unavoidable biochemical noise perturbing the gradients. We focus on gradient proteins with first order reaction kinetics. Systems of this type have been experimentally characterised in both developmental and cell biology settings. For a single gradient we show that, through time-averaging, great precision can potentially be achieved even with very low protein copy numbers. As a second example, we investigate the ability of a system with oppositely directed gradients to find its centre. With this mechanism, positional precision close to the centre improves more slowly with increasing averaging time, and so longer averaging times or higher copy numbers are required for high precision. For both single and double gradients, we demonstrate the existence of optimal length scales for the gradients, where precision is maximized, as well as analyzing how precision depends on the size of the concentration measuring apparatus. Our results provide fundamental constraints on the positional precision supplied by concentration gradients in various contexts, including both in developmental biology and also within a single cell.Comment: 24 pages, 2 figure

Organellar carbon metabolism is co-ordinated with distinct developmental phases of secondary xylem

Subcellular compartmentation of plant biosynthetic pathways in the mitochondria and plastids requires coordinated regulation of nuclear encoded genes, and the role of these genes has been largely ignored by wood researchers. In this study, we constructed a targeted systems genetics coexpression network of xylogenesis in Eucalyptus using plastid and mitochondrial carbon metabolic genes and compared the resulting clusters to the aspen xylem developmental series. The constructed network clusters reveal the organization of transcriptional modules regulating subcellular metabolic functions in plastids and mitochondria. Overlapping genes between the plastid and mitochondrial networks implicate the common transcriptional regulation of carbon metabolism during xylem secondary growth. We show that the central processes of organellar carbon metabolism are distinctly coordinated across the developmental stages of wood formation and are specifically associated with primary growth and secondary cell wall deposition. We also demonstrate that, during xylogenesis, plastid-targeted carbon metabolism is partially regulated by the central clock for carbon allocation towards primary and secondary xylem growth, and we discuss these networks in the context of previously established associations with wood-related complex traits. This study provides a new resolution into the integration and transcriptional regulation of plastid- and mitochondrial-localized carbon metabolism during xylogenesis

Sequence-specific protein aggregation generates defined protein knockdowns in plants

Protein aggregation is determined by short (5-15 amino acids) aggregation-prone regions (APRs) of the polypeptide sequence that self-associate in a specific manner to form beta-structured inclusions. Here, we demonstrate that the sequence specificity of APRs can be exploited to selectively knock down proteins with different localization and function in plants. Synthetic aggregation-prone peptides derived from the APRs of either the negative regulators of the brassinosteroid (BR) signaling, the glycogen synthase kinase 3/Arabidopsis SHAGGY-like kinases (GSK3/ASKs), or the starch-degrading enzyme alpha-glucan water dikinase were designed. Stable expression of the APRs in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays) induced aggregation of the target proteins, giving rise to plants displaying constitutive BR responses and increased starch content, respectively. Overall, we show that the sequence specificity of APRs can be harnessed to generate aggregation-associated phenotypes in a targeted manner in different subcellular compartments. This study points toward the potential application of induced targeted aggregation as a useful tool to knock down protein functions in plants and, especially, to generate beneficial traits in crops

In vitro and in vivo screening for novel essential cell-envelope proteins in Pseudomonas aeruginosa

The Gram-negative bacterium Pseudomonas aeruginosa represents a prototype of multi-drug resistant opportunistic pathogens for which novel therapeutic options are urgently required. In order to identify new candidates as potential drug targets, we combined large-scale transposon mutagenesis data analysis and bioinformatics predictions to retrieve a set of putative essential genes which are conserved in P. aeruginosa and predicted to encode cell envelope or secreted proteins. By generating unmarked deletion or conditional mutants, we confirmed the in vitro essentiality of two periplasmic proteins, LptH and LolA, responsible for lipopolysaccharide and lipoproteins transport to the outer membrane respectively, and confirmed that they are important for cell envelope stability. LptH was also found to be essential for P. aeruginosa ability to cause infection in different animal models. Conversely, LolA-depleted cells appeared only partially impaired in pathogenicity, indicating that this protein likely plays a less relevant role during bacterial infection. Finally, we ruled out any involvement of the other six proteins under investigation in P. aeruginosa growth, cell envelope stability and virulence. Besides proposing LptH as a very promising drug target in P. aeruginosa, this study confirms the importance of in vitro and in vivo validation of potential essential genes identified through random transposon mutagenesis