An Efficient, Amine-Specific, and Cost-Effective Method for TMT 6/11-plex Labeling Improves the Proteome Coverage, Quantitative Accuracy and Precision.

Tandem mass tags (TMT) are widely used in proteomics to simultaneously quantify multiple samples in a single experiment. The tags can be easily added to the primary amines of peptides/proteins through chemical reactions. In addition to amines, TMT reagents also partially react with the hydroxyl groups of serine, threonine, and tyrosine residues under alkaline conditions, which significantly compromises the analytical sensitivity and precision. Under alkaline conditions, reducing the TMT molar excess can partially mitigate overlabeling of histidine-free peptides, but has a limited effect on peptides containing histidine and hydroxyl groups. Here, we present a method under acidic conditions to suppress overlabeling while efficiently labeling amines, using only one-fifth of the TMT amount recommended by the manufacturer. In a deep-scale analysis of a yeast/human two-proteome sample, we systematically evaluated our method against the manufacturer's method and a previously reported TMT-reduced method. Our method reduced overlabeled peptides by 9-fold and 6-fold, respectively, resulting in the substantial enhancement in peptide/protein identification rates. More importantly, the quantitative accuracy and precision were improved as overlabeling was reduced, endowing our method with greater statistical power to detect 42% and 12% more statistically significant yeast proteins compared to the standard and TMT-reduced methods, respectively. Mass spectrometric data have been deposited in the ProteomeXchange Consortium via the iProX partner repository with the data set identifier PXD047052.

Construction of an economical xylose-utilizing Saccharomyces cerevisiae and its ethanol fermentation.

Traditional industrial Saccharomyces cerevisiae could not metabolize xylose due to the lack of a specific enzyme system for the reaction from xylose to xylulose. This study aims to metabolically remould industrial S. cerevisiae for the purpose of utilizing both glucose and xylose with high efficiency. Heterologous gene xylA from Piromyces and homologous genes related to xylose utilization were selected to construct expression cassettes and integrated into genome. The engineered strain was domesticated with industrial material under optimizing conditions subsequently to further improve xylose utilization rates. The resulting S. cerevisiae strain ABX0928-0630 exhibits a rapid growth rate and possesses near 100% xylose utilization efficiency to produce ethanol with industrial material. Pilot-scale fermentation indicated the predominant feature of ABX0928-0630 for industrial application, with ethanol yield of 0.48 g/g sugars after 48 hours and volumetric xylose consumption rate of 0.87 g/l/h during the first 24 hours. Transcriptome analysis during the modification and domestication process revealed a significant increase in the expression level of pathways associated with sugar metabolism and sugar sensing. Meanwhile, genes related to glycerol lipid metabolism exhibited a pattern of initial increase followed by a subsequent decrease, providing a valuable reference for the construction of efficient xylose-fermenting strains.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast.

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed-remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

Elevated energy costs of biomass production in mitochondrial respiration-deficient Saccharomyces cerevisia.

Microbial growth requires energy for maintaining the existing cells and producing components for the new ones. Microbes therefore invest a considerable amount of their resources into proteins needed for energy harvesting. Growth in different environments is associated with different energy demands for growth of yeast Saccharomyces cerevisiae, although the cross-condition differences remain poorly characterized. Furthermore, a direct comparison of the energy costs for the biosynthesis of the new biomass across conditions is not feasible experimentally; computational models, on the contrary, allow comparing the optimal metabolic strategies and quantify the respective costs of energy and nutrients. Thus in this study, we used a resource allocation model of S. cerevisiae to compare the optimal metabolic strategies between different conditions. We found that S. cerevisiae with respiratory-impaired mitochondria required additional energetic investments for growth, while growth on amino acid-rich media was not affected. Amino acid supplementation in anaerobic conditions also was predicted to rescue the growth reduction in mitochondrial respiratory shuttle-deficient mutants of S. cerevisiae. Collectively, these results point to elevated costs of resolving the redox imbalance caused by de novo biosynthesis of amino acids in mitochondria. To sum up, our study provides an example of how resource allocation modeling can be used to address and suggest explanations to open questions in microbial physiology.

Assessment of chalkiness index of Sake rice using transmission imaging.

The higher chalkiness level of the white core kernel is prone to breakage during the high degree polishing. So, grading white core kernel based on chalkiness level is crucial to making premium quality Sake (rice wine) in the brewing industry. The chalkiness level in the white core kernel is currently performed destructively. Thus, a chalkiness index is required to assess the level in the white core kernel. This research assesses the white core rice kernel based on the chalkiness index non-destructively. Here, the optical transmission property in the visible to near-infrared (VIS-NIR) region of rice was measured using a V-670 spectrophotometer equipped with an integrating sphere to investigate the variation of chalkiness level rice samples. The images were then acquired by transmission mode of four types of intact Sake rice kernel using blue light-emitting diodes (LEDs), green, red, and NIR LEDs in which the peak wavelength of the LEDs was 465 nm, 525 nm, 630 nm, and 830 nm, respectively. The result indicates that the rice samples were more penetrated and better visualized chalkiness by light in the NIR region. Therefore, the wavelength region in NIR showed better discrimination between transparent and opaque parts in white core's Sake rice. Furthermore, the proposed chalkiness index was inversely correlated with the gray-level intensity of the transmittance image. This gray value was significantly correlated (R2 = 0.89) with the chalkiness index in the NIR region. So, gray values of NIR transmittance images were identified as sensitive for chalkiness index, which would be applied for sorting the white core kernel with different levels of chalkiness in the Sake brewing industry.

Yeast has evolved to minimize protein resource cost for synthesizing amino acids.

Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynthesis of the 20 proteinogenic amino acids. Previous studies showed that less energetically costly amino acids are more abundant in the proteomes of bacteria that survive under energy-limited conditions, but the energy cost of synthesizing amino acids was reported to be weakly associated with the amino acid usage in Saccharomyces cerevisiae Here we present a modeling framework to estimate the protein cost of synthesizing each amino acid (i.e., the protein mass required for supporting one unit of amino acid biosynthetic flux) and the glucose cost (i.e., the glucose consumed per amino acid synthesized). We show that the logarithms of the relative abundances of amino acids in S. cerevisiae's proteome correlate well with the protein costs of synthesizing amino acids (Pearson's r = -0.89), which is better than that with the glucose costs (Pearson's r = -0.5). Therefore, we demonstrate that S. cerevisiae tends to minimize protein resource, rather than glucose or energy, for synthesizing amino acids.

Assessment of Cre-lox and CRISPR-Cas9 as tools for recycling of multiple-integrated selection markers in Saccharomyces cerevisiae.

We evaluated the Cre-lox and CRISPR-Cas9 systems as marker-recycling tools in Saccharomyces cerevisiae recombinants containing multiple-integrated expression cassettes. As an initial trial, we constructed rDNA-nontranscribed spacer- or Ty4-based multiple integration vectors containing the URA3 marker flanked by the loxP sequence. Integrants harboring multiple copies of tHMG1 and NNV-CP expression cassettes were obtained and subsequently transformed with the Cre plasmid. However, the simultaneous pop-out of the expression cassettes along with the URA3 marker hampered the use of Cre-lox as a marker-recycling tool in multiple integrants. As an alternative, we constructed a set of CRISPR-Cas9-gRNA vectors containing gRNA targeted to auxotrophic marker genes. Transformation of multiple integrants of tHMG1 and NNV-CP cassettes by the Cas9-gRNA vector in the presence of the URA3 (stop) donor DNA fragments generated the Ura- transformants retaining multiple copies of the expression cassettes. CRISPR-Cas9-based inactivation led to the recycling of the other markers, HIS3, LEU2, and TRP1, without loss of expression cassettes in the recombinants containing multiple copies of tHMG1, NNV-CP, and SfBGL1 cassettes, respectively. Reuse of the same selection marker in marker-inactivated S. cerevisiae was validated by multiple integrations of the TrEGL2 cassette into the S. cerevisiae strain expressing SfBGL1. These results demonstrate that introducing stop codons into selection marker genes using the CRISPR-Cas9 system with donor DNA fragments is an efficient strategy for markerrecycling in multiple integrants. In particular, the continual reuse of auxotrophic markers would facilitate the construction of a yeast cell factory containing multiple copies of expression cassettes without antibiotic resistance genes.

Assessment of micropollutants toxicity by using a modified Saccharomyces cerevisiae model.

Environment can be affected by a variety of micropollutants. In this paper, we develop a system to assess the toxicity on an environmental sample, based on the expression of a nanoluciferase under the control of the STB5 promotor in a yeast. The STB5 gene encodes for a transcription factor involved in a pleiotropic drug resistance and in the oxidative stress response. The response of the modified yeast was assessed using 42 micropollutants belonging to different families (antibiotics, pain killers, hormones, plasticizers, pesticides, etc.). Among them, 26 induced an increase of the bioluminescence for concentration ranges from pg.L-1 to ng.L-1. Surprisingly, for concentrations higher than 100 ng.L-1, no response can be observed, suggesting that other mechanisms are involved when the stress increases. Analyzing the different responses obtained, we highlighted six nonmonotonic types of responses. The type of response seems to be independent of the properties of the compounds (polarity, toxicology, molecular weight) and of their family. In conclusion, we highlighted that a cellular response exists for very low exposition to environmental concentration of micropollutants and that it was necessary to explore the cellular mechanisms involved at very low concentration to provide a better risk assessment.

A prion accelerates proliferation at the expense of lifespan.

In fluctuating environments, switching between different growth strategies, such as those affecting cell size and proliferation, can be advantageous to an organism. Trade-offs arise, however. Mechanisms that aberrantly increase cell size or proliferation-such as mutations or chemicals that interfere with growth regulatory pathways-can also shorten lifespan. Here we report a natural example of how the interplay between growth and lifespan can be epigenetically controlled. We find that a highly conserved RNA-modifying enzyme, the pseudouridine synthase Pus4/TruB, can act as a prion, endowing yeast with greater proliferation rates at the cost of a shortened lifespan. Cells harboring the prion grow larger and exhibit altered protein synthesis. This epigenetic state, [BIG+] (better in growth), allows cells to heritably yet reversibly alter their translational program, leading to the differential synthesis of dozens of proteins, including many that regulate proliferation and aging. Our data reveal a new role for prion-based control of an RNA-modifying enzyme in driving heritable epigenetic states that transform cell growth and survival.

Cells make different proteins to perform different tasks. Each protein is a long chain of building blocks called amino acids that must fold into a particular shape before it can be useful. Some proteins can fold in more than one way, a normal form and a 'prion' form. Prions are unusual in that they can force normally folded proteins with the same amino acid sequence as them to refold into new prions. This means that a single prion can make many more that are inherited when cells divide. Some prions can cause disease, but others may be beneficial. Pus4 is a yeast protein that is typically involved in modifying ribonucleic acids, molecules that help translate genetic information into new proteins. Sometimes Pus4 can adopt a beneficial prion conformation called [BIG⁺]. When yeast cells have access to plenty of nutrients, [BIG⁺] helps them grow faster and larger, but this comes at the cost of a shorter lifespan. Garcia, Campbell et al. combined computational modeling and experiments in baker's yeast (Saccharomyces cerevisiae) to investigate the role of [BIG⁺]. They found that the prion accelerated protein production, leading to both faster growth and a shorter lifespan in these cells, even without any changes in gene sequence. Garcia, Campbell et al.'s findings explain the beneficial activity of prion proteins in baker's yeast cells. The results also describe how cells balance a tradeoff between growth and lifespan without any changes in the genome. This helps to highlight that genetics do not always explain the behaviors of cells, and further methods are needed to better understand cell biology.

Assessment of Submitochondrial Protein Localization in Budding Yeast Saccharomyces cerevisiae.

Despite recent advances in the characterization of yeast mitochondrial proteome, the submitochondrial localization of a significant number of proteins remains elusive. Here, we describe a robust and effective method for determining the suborganellar localization of yeast mitochondrial proteins, which is considered a fundamental step during mitochondrial protein function elucidation. This method involves an initial step that consists of obtaining highly pure intact mitochondria. These mitochondrial preparations are then subjected to a subfractionation protocol consisting of hypotonic shock (swelling) and incubation with proteinase K (protease). During swelling, the outer mitochondrial membrane is selectively disrupted, allowing the proteinase K to digest proteins of the intermembrane space compartment. In parallel, to obtain information about the topology of membrane proteins, the mitochondrial preparations are initially sonicated, and then subjected to alkaline extraction with sodium carbonate. Finally, after centrifugation, the pellet and supernatant fractions from these different treatments are analyzed by SDS-PAGE and western blot. The submitochondrial localization as well as the membrane topology of the protein of interest is obtained by comparing its western blot profile with known standards.

Development of a method for heat shock stress assessment in yeast based on transcription of specific genes.

All living cells, including yeast cells, are challenged by different types of stresses in their environments and must cope with challenges such as heat, chemical stress, or oxidative damage. By reversibly adjusting the physiology while maintaining structural and genetic integrity, cells can achieve a competitive advantage and adapt environmental fluctuations. The yeast Saccharomyces cerevisiae has been extensively used as a model for study of stress responses due to the strong conservation of many essential cellular processes between yeast and human cells. We focused here on developing a tool to detect and quantify early responses using specific transcriptional responses. We analyzed the published transcriptional data on S. cerevisiae DBY strain responses to 10 different stresses in different time points. The principal component analysis (PCA) and the Pearson analysis were used to assess the stress response genes that are highly expressed in each individual stress condition. Except for these stress response genes, we also identified the reference genes in each stress condition, which would not be induced under stress condition and show stable transcriptional expression over time. We then tested our candidates experimentally in the CEN.PK strain. After data analysis, we identified two stress response genes (UBI4 and RRP) and two reference genes (MEX67 and SSY1) under heat shock (HS) condition. These genes were further verified by real-time PCR at mild (42°C), severe (46°C), to lethal temperature (50°C), respectively.

A comprehensive mechanism for 5-carboxylcytosine-induced transcriptional pausing revealed by Markov state models.

RNA polymerase II (Pol II) surveils the genome, pausing as it encounters DNA lesions and base modifications and initiating signals for DNA repair among other important regulatory events. Recent work suggests that Pol II pauses at 5-carboxycytosine (5caC), an epigenetic modification of cytosine, because of a specific hydrogen bond between the carboxyl group of 5caC and a specific residue in fork loop 3 of Pol II. This hydrogen bond compromises productive NTP binding and slows down elongation. Apart from this specific interaction, the carboxyl group of 5caC can potentially interact with numerous charged residues in the cleft of Pol II. However, it is not clear how other interactions between Pol II and 5caC contribute to pausing. In this study, we use Markov state models (a type of kinetic network models) built from extensive molecular dynamics simulations to comprehensively study the impact of 5caC on Pol II translocation. We describe two translocation intermediates with specific interactions that prevent the template base from loading into the Pol II active site. In addition to the previously observed state with 5caC constrained by fork loop 3, we discovered a new intermediate state with a hydrogen bond between 5caC and fork loop 2. Surprisingly, we find that 5caC may curb translocation by suppressing kinking of the helix bordering the active site (the bridge helix) because its high flexibility is critical to translocation. Our work provides new insights into how epigenetic modifications of genomic DNA can modulate Pol II translocation, inducing pauses in transcription.

Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae.

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar's classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.

A novel assessment system of toxicity and stability of CuO nanoparticles via copper super sensitive Saccharomyces cerevisiae mutants.

CuO nanoparticles (CuO-NPs) toxicity in organisms is contributed mainly through the copper uptake by both the ionic and nanoparticle form. However, the relative uptake ratio and bioavailability of the two different forms is not well known due to a lack of sensitive and effective assessment systems. We developed a series of both copper resistant and hyper sensitive Saccharomyces cerevisiae mutants to investigate and compare the effects of CuO-NPs and dissolved copper (CuCl2), on the eukaryote with the purpose of quantitating the relative contributions of nanoparticles and dissolved species for Cu uptake. We observed the toxicity of 10 mM CuO-NPs for copper sensitive strains is equal to that of 0.5 mM CuCl2 and the main toxic effect is most likely generated from oxidative stress through reactive oxygen species (ROS) production. About 95% CuO-NPs exist in nanoparticle form under neutral environmental conditions. Assessing the cellular metal content of wild type and copper transporter 1(CTR1) knock out cells showed that endocytosis is the major absorption style for CuO-NPs. This study also found a similar toxicity of Ag for both 10 mM Ag-NPs and 0.2 mM AgNO3 in the copper super sensitive strains. Our study revealed the absorption mechanism of soluble metal based nanomaterials CuO-NPs and Ag-NPs as well as provided a sensitive and delicate system to precisely evaluate the toxicity and stability of nanoparticles.

Design of a MAPK signalling cascade balances energetic cost versus accuracy of information transmission.

Cellular processes are inherently noisy, and the selection for accurate responses in presence of noise has likely shaped signalling networks. Here, we investigate the trade-off between accuracy of information transmission and its energetic cost for a mitogen-activated protein kinase (MAPK) signalling cascade. Our analysis of the pheromone response pathway of budding yeast suggests that dose-dependent induction of the negative transcriptional feedbacks in this network maximizes the information per unit energetic cost, rather than the information transmission capacity itself. We further demonstrate that futile cycling of MAPK phosphorylation and dephosphorylation has a measurable effect on growth fitness, with energy dissipation within the signalling cascade thus likely being subject to evolutionary selection. Considering optimization of accuracy versus the energetic cost of information processing, a concept well established in physics and engineering, may thus offer a general framework to understand the regulatory design of cellular signalling systems.

Quantitative assessment of the determinant structural differences between redox-active and inactive glutaredoxins.

Class I glutaredoxins are enzymatically active, glutathione-dependent oxidoreductases, whilst class II glutaredoxins are typically enzymatically inactive, Fe-S cluster-binding proteins. Enzymatically active glutaredoxins harbor both a glutathione-scaffold site for reacting with glutathionylated disulfide substrates and a glutathione-activator site for reacting with reduced glutathione. Here, using yeast ScGrx7 as a model protein, we comprehensively identified and characterized key residues from four distinct protein regions, as well as the covalently bound glutathione moiety, and quantified their contribution to both interaction sites. Additionally, we developed a redox-sensitive GFP2-based assay, which allowed the real-time assessment of glutaredoxin structure-function relationships inside living cells. Finally, we employed this assay to rapidly screen multiple glutaredoxin mutants, ultimately enabling us to convert enzymatically active and inactive glutaredoxins into each other. In summary, we have gained a comprehensive understanding of the mechanistic underpinnings of glutaredoxin catalysis and have elucidated the determinant structural differences between the two main classes of glutaredoxins.

The C-terminal tail of the yeast mitochondrial transcription factor Mtf1 coordinates template strand alignment, DNA scrunching and timely transition into elongation.

Mitochondrial RNA polymerases depend on initiation factors, such as TFB2M in humans and Mtf1 in yeast Saccharomyces cerevisiae, for promoter-specific transcription. These factors drive the melting of promoter DNA, but how they support RNA priming and growth was not understood. We show that the flexible C-terminal tails of Mtf1 and TFB2M play a crucial role in RNA priming by aiding template strand alignment in the active site for high-affinity binding of the initiating nucleotides. Using single-molecule fluorescence approaches, we show that the Mtf1 C-tail promotes RNA growth during initiation by stabilizing the scrunched DNA conformation. Additionally, due to its location in the path of the nascent RNA, the C-tail of Mtf1 serves as a sensor of the RNA-DNA hybrid length. Initially, steric clashes of the Mtf1 C-tail with short RNA-DNA hybrids cause abortive synthesis but clashes with longer RNA-DNA trigger conformational changes for the timely release of the promoter DNA to commence the transition into elongation. The remarkable similarities in the functions of the C-tail and σ3.2 finger of the bacterial factor suggest mechanistic convergence of a flexible element in the transcription initiation factor that engages the DNA template for RNA priming and growth and disengages when needed to generate the elongation complex.

Biocompatibility assessment of Fe3O4 nanoparticles using Saccharomyces cerevisiae as a model organism.

Using Saccharomyces cerevisiae as an experimental model, the potential toxicological effects of Fe3O4 nanoparticles (Fe3O4-NPs) were investigated following exposure to 0-600 mg/L for 24 h. Results revealed that cell proliferation was significantly inhibited by Fe3O4-NPs with an IC50 value of 326.66 mg/L. Mortality showed a concentration-dependent increase, and the highest concentration in this study (600 mg/L) resulted in 22.30% mortality. In addition, Effects on proliferation and mortality were accounted for Fe3O4-NPs rather than iron ion released from Fe3O4-NPs. Scanning and transmission electron microscope observation showed that Fe3O4-NPs extensively attached on the cell surfaces, causing cells to deform and shrink. Moreover, Fe3O4-NPs could be internalized in S. cerevisiae cells via endocytosis and then be distributed in cytoplasm and vesicles. The data of uptake kinetics demonstrated that the maximal accumulation (4.898 mg/g) was reached at 15 h. Besides, percentage of late apoptosis/necrosis was observably increased (p < 0.01) at 600 mg/L (15.80%), and the expression levels of apoptosis-related genes (SOD, Yca1 and Nuc1) were dramatically increased following exposure to Fe3O4-NPs for 24 h. As expected, mitochondrial transmembrane potential was significantly decreased (p < 0.01) at 50-600 mg/L, and biomarkers of oxidative stress (ROS, CAT and SOD) were also markedly changed following exposure. Altogether, the combined results so far indicated Fe3O4-NPs could induce S. cerevisiae cell apoptosis that mediated by mitochondrial impairment and oxidative stress.

LePrimAlign: local entropy-based alignment of PPI networks to predict conserved modules.

BACKGROUND: Cross-species analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved interaction patterns. Identifying such conserved substructures between PPI networks of different species increases our understanding of the principles deriving evolution of cellular organizations and their functions in a system level. In recent years, network alignment techniques have been applied to genome-scale PPI networks to predict evolutionary conserved modules. Although a wide variety of network alignment algorithms have been introduced, developing a scalable local network alignment algorithm with high accuracy is still challenging. RESULTS: We present a novel pairwise local network alignment algorithm, called LePrimAlign, to predict conserved modules between PPI networks of three different species. The proposed algorithm exploits the results of a pairwise global alignment algorithm with many-to-many node mapping. It also applies the concept of graph entropy to detect initial cluster pairs from two networks. Finally, the initial clusters are expanded to increase the local alignment score that is formulated by a combination of intra-network and inter-network scores. The performance comparison with state-of-the-art approaches demonstrates that the proposed algorithm outperforms in terms of accuracy of identified protein complexes and quality of alignments. CONCLUSION: The proposed method produces local network alignment of higher accuracy in predicting conserved modules even with large biological networks at a reduced computational cost.

DNMHMM: An approach to identify the differential nucleosome regions in multiple cell types based on a Hidden Markov Model.

Nucleosome occupancy changes across cell types and environmental conditions and such changes often have profound influence in transcription. It's of importance to identify the differential nucleosome regions (DNRs) where the nucleosome occupancy level differs across cell types. Here we developed DNMHMM, a Hidden Markov Model (HMM) based algorithm, to detect the DNRs with nucleosomal DNA sequenced dataset. The performance evaluation indicates that DNMHMM is advisable for multi-cell type comparison. Upon testing this model in yeast mutants, where the modifiable histone residues were mutated into alanine, we found that DNA sequences of the dynamic nucleosomes lack 10-11 bp periodicities and harbor binding motifs of the nucleosome remodelling complex. Moreover, the highly expressed genes have more dynamic nucleosomes at promoters. We further compared nucleosome occupancy between resting and activated human CD4+ T cells with this model. It was revealed that during the activation of CD4+ T cells, dynamic nucleosomes are enriched at regulatory sites, hence, up to some extent can affect the gene expression level. Taken together, DNMHMM offers the possibility to access precise nucleosome dynamics among multiple cell types and also can describe the closer association between nucleosome and transcription.