Exploring the binding mechanisms of thermally and ultrasonically induced molten globule-like ß-lactoglobulin with heptanal as revealed by multi-spectroscopic techniques and molecular simulation.

This work employed the model protein ß-lactoglobulin (BLG) to investigate the contribution of microstructural changes to regulating the interaction patterns between protein and flavor compounds through employing computer simulation and multi-spectroscopic techniques. The formation of molten globule (MG) state-like protein during the conformational evolution of BLG, in response to ultrasonic (UC) and heat (HT) treatments, was revealed through multi-spectroscopic characterization. Differential MG structures were distinguished by variations in surface hydrophobicity and the microenvironment of tryptophan residues. Fluorescence quenching measurements indicated that the formation of MG enhanced the binding affinity of heptanal to protein. LC-MS/MS and NMR revealed the covalent bonding between heptanal and BLG formed by Michael addition and Schiff-base reactions, and MG-like BLG exhibited fewer chemical shift residues. Molecular docking and molecular dynamics simulation confirmed the synergistic involvement of hydrophobic interactions and hydrogen bonds in shaping BLG-heptanal complexes thus promoting the stability of BLG structures. These findings indicated that the production of BLG-heptanal complexes was driven synergistically by non-covalent and covalent bonds, and their interaction processes were influenced by processes-induced formation of MG potentially tuning the release and retention behaviors of flavor compounds.

Nucleic Acid Amplification-Free Bioluminescent Detection of MicroRNAs with High Sensitivity and Accuracy Based on Controlled Target Degradation.

Accurate and sensitive detection of microRNAs is crucial to clinical diagnosis and therapy. Most of microRNA assays require target conversion in combination with nucleic acid amplification to improve the detection sensitivity, which may compromise the assay accuracy and specificity. Herein we report a sensitive bioluminescent method for microRNA assay on the basis of controlled target degradation without target conversion and nucleic acid amplification. In this assay, the target microRNA can be specifically degraded by exonuclease III after hybridization to its complementary probe, releasing adenosine monophosphate (AMP) from microRNA itself. The AMP then triggers an efficient bioluminescence generation system to produce a strong bioluminescence signal. This assay is highly sensitive with zero-background signal and a detection limit of 7.6 fM even without target amplification, and it can discriminate the single-nucleotide difference among microRNA family members with extremely high discrimination ratio. With the assistance of magnetic separation to eliminate the interference of endogenous ATP, ADP, and AMP in sample matrix, this assay can be further applied to absolute quantification of microRNAs in cancer cells and tissues from lung cancer patients, holding great potential in biomedical research and clinical diagnosis.

Controllable Mismatched Ligation for Bioluminescence Screening of Known and Unknown Mutations.

Single-nucleotide polymorphisms (SNPs) are closely related to human diseases and individual drug responses, and the accurate detection of SNPs is crucial to both clinical diagnosis and development of personalized medicine. Among various SNPs detection methods, ligase detection reaction (LDR) has shown great potential due to its low detection limit and excellent specificity. However, frequent involvement of expensive labels increases the experimental cost and compromises the assay efficiency, and the requirement of careful predesigned probes limits it to only known SNPs assays. In this research, we develop a controllable mismatched ligation for bioluminescence screening of both known and unknown mutations. Especially, the ligation specificity of E. coli ligase is tunable under different experimental conditions. The mismatches locating on the 3'-side of the nick cannot be ligated efficiently by E. coli ligase, whereas all mismatches locating on the 5'-side of the nick can be ligated efficiently by E. coli ligase. We design a 3'-discriminating probe (3'-probe) for the discrimination of known mutation and introduce a T7 Endo I for the detection of unknown mutation. With the integration of bioluminescence monitoring of ligation byproduct adenosine 5'-monophosphate (AMP), both known and unknown SNPs can be easily detected without the involvement of any expensive labels and labor-intensive separation. This method is simple, homogeneous, label-free, and cost-effective and may provide a valuable complement to current sequencing technologies for disease diagnostics, personalized medicine, and biomedical research.

Sensitive detection of point mutation using exponential strand displacement amplification-based surface enhanced Raman spectroscopy.

Accurate identification of point mutation is particularly imperative in the field of biomedical research and clinical diagnosis. Here, we develop a sensitive and specific method for point mutation assay using exponential strand displacement amplification (SDA)-based surface enhanced Raman spectroscopy (SERS). In this method, a discriminating probe and a hairpin probe are designed to specifically recognize the sequence of human K-ras gene. In the presence of K-ras mutant target (C→T), the 3'-terminal of discriminating probe and the 5'-terminal of hairpin probe can be ligated to form a SDA template. Subsequently, the 3'-terminal of hairpin probe can function as a primer to initiate the SDA reaction, producing a large amount of triggers. The resultant triggers can further hybridize with the discriminating probes to initiate new rounds of SDA reaction, leading to an exponential amplification reaction. With the addition of capture probe-modified gold nanoparticles (AuNPs) and the Rox-labeled reporter probes, the amplified triggers can be assembled on the surface of AuNPs through the formation of sandwich hybrids of capture probe-trigger-reporter probe, generating a strong Raman signal. While in the presence of K-ras wild-type target (C), neither ligation nor SDA reaction can be initiated and no Raman signal is observed. The proposed method exhibits high sensitivity with a detection limit of 1.4pM and can accurately discriminate as low as 1% variant frequency from the mixture of mutant target and wild-type target. Importantly, this method can be further applied to analyze the mutant target in the spiked HEK293T cell lysate, holding great potential for genetic analysis and disease prognosis.

Complementary iTRAQ proteomics and RNA-seq transcriptomics reveal multiple levels of regulation in response to nitrogen starvation in Synechocystis sp. PCC 6803.

Sequential adaptation to environmental stress needs complex regulation at different cellular levels in cyanobacteria. To uncover the regulatory mechanism in response to nitrogen starvation, we investigated the genome-wide correlation between protein abundance and gene expression in a model cyanobacterium Synechocystis sp. PCC 6803 using complementary quantitative iTRAQ proteomics and RNA-seq transcriptomics. Consistent with the cell growth inhibition, proteomic analysis indicated phase-dependent down-regulation of proteins related to nitrogen metabolism, ribosome complexes, glycolysis pathway and tricarboxylic acid (TCA) cycles by nitrogen starvation. Transcriptomic analysis also showed that genes related to "Photosynthesis", "Protein synthesis" and "Energy metabolism" were significantly down-regulated by nitrogen starvation. Interestingly, the concordance between protein abundances and their corresponding mRNAs exhibited a functional categories-dependent pattern, with some categories, such as "Protein synthesis" and "Energy metabolism", having a relatively high correlation, while others even with numerous discordant changes in protein-mRNA pairs, indicated divergent regulation of transcriptional and post-transcriptional processes. In particular, an increased abundance of proteins related to "Photosynthesis" upon nitrogen starvation was found to be reversely correlated with the down-regulation of their corresponding mRNAs. In addition, two metabolic modules highly correlated with nitrogen starvation were identified by a co-expression network analysis, and were found to contain mostly photosynthetic proteins and hypothetical proteins, respectively. We further confirmed the involvement of the photosynthetic genes in nitrogen starvation tolerance by constructing and analyzing the psbV gene deletion mutant.

Integrated proteomic and transcriptomic analysis reveals novel genes and regulatory mechanisms involved in salt stress responses in Synechocystis sp. PCC 6803.

Salt stress is a common stress that limits growth and productivity of photosynthetic microbes in natural environments. Although cellular responses of a model cyanobacterium Synechocystis sp. PCC6803 to high and changing salt concentration have been studied, it remains undefined of the gene components and their regulation in the long-term salt acclimation networks. In this study, we performed an integrated study coupling a quantitative iTRAQ-LC-MS/MS proteomics and a next-generation sequencing-based RNA-seq transcriptomics on Synechocystis under salt stress for an extended period of time. Comparative quantification of protein abundances led to the identification of 68 and 108 proteins differentially regulated by salt treatment at 24 and 48 h, respectively. RNA-seq transcriptomic analysis showed that genes involved in energy metabolism and protein synthesis, and genes encoding hypothetical proteins responded to salt stress in a phase-dependent pattern. Notably, a gene encoding CO2-uptake-related protein (CupA) and three genes encoding hypothetical proteins were induced significantly at either transcript or protein level after long-term salt stress. Gene knockout and comparative growth analysis demonstrated that these four genes were involved in salt tolerance in Synechocystis. In addition, a complementary proteome and transcriptome analysis showed that concordance between protein abundances and their corresponding mRNAs varied significantly between various gene-protein pairs, indicating divergent regulation of transcriptional and post-transcriptional processes during salt stress adaptation in Synechocystis. The study provided new insights on genes and regulatory mechanism involved in salt stress response in Synechocystis.

Systematic characterization of hypothetical proteins in Synechocystis sp. PCC 6803 reveals proteins functionally relevant to stress responses.

We described here a global detection and functional inference of hypothetical proteins involved in stress response in Synechocystis sp. PCC 6803. In the study, we first applied an iTRAQ-LC-MS/MS based quantitative proteomics to the Synechocystis cells grown under five stress conditions. The analysis detected a total of 807 hypothetical proteins with high confidence. Among them, 480 were differentially regulated. We then applied a Weighted Gene Co-expression Network Analysis approach to construct transcriptional networks for Synechocystis under nutrient limitation and osmotic stress conditions using transcriptome datasets. The analysis showed that 305 and 467 coding genes of hypothetical proteins were functionally relevant to nutrient limitation and osmotic stress, respectively. A comparison of responsive hypothetical proteins to all stress conditions allowed identification of 22 hypothetical proteins commonly responsive to all stresses, suggesting they may be part of the core stress responses in Synechocystis. Finally, functional inference of these core stress responsive proteins using both sequence similarity and non-similarity approaches was conducted. The study provided new insights into the stress response networks in Synechocystis, and also demonstrated that a combination of experimental "OMICS" and bioinformatics methodologies could improve functional annotation for hypothetical proteins.

RNA-seq based identification and mutant validation of gene targets related to ethanol resistance in cyanobacterial Synechocystis sp. PCC 6803.

BACKGROUND: Fermentation production of biofuel ethanol consumes agricultural crops, which will compete directly with the food supply. As an alternative, photosynthetic cyanobacteria have been proposed as microbial factories to produce ethanol directly from solar energy and CO2. However, the ethanol productivity from photoautotrophic cyanobacteria is still very low, mostly due to the low tolerance of cyanobacterial systems to ethanol stress. RESULTS: To build a foundation necessary to engineer robust ethanol-producing cyanobacterial hosts, in this study we applied a quantitative transcriptomics approach with a next-generation sequencing technology, combined with quantitative reverse-transcript PCR (RT-PCR) analysis, to reveal the global metabolic responses to ethanol in model cyanobacterial Synechocystis sp. PCC 6803. The results showed that ethanol exposure induced genes involved in common stress responses, transporting and cell envelope modification. In addition, the cells can also utilize enhanced polyhydroxyalkanoates (PHA) accumulation and glyoxalase detoxication pathway as means against ethanol stress. The up-regulation of photosynthesis by ethanol was also further confirmed at transcriptional level. Finally, we used gene knockout strains to validate the potential target genes related to ethanol tolerance. CONCLUSION: RNA-Seq based global transcriptomic analysis provided a comprehensive view of cellular response to ethanol exposure. The analysis provided a list of gene targets for engineering ethanol tolerance in cyanobacterium Synechocystis.

Quantitative iTRAQ LC-MS/MS proteomics reveals metabolic responses to biofuel ethanol in cyanobacterial Synechocystis sp. PCC 6803.

Recent progress in metabolic engineering has led to autotrophic production of ethanol in various cyanobacterial hosts. However, cyanobacteria are known to be sensitive to ethanol, which restricts further efforts to increase ethanol production levels in these renewable host systems. To understand the mechanisms of ethanol tolerance so that engineering more robust cyanobacterial hosts can be possible, in this study, the responses of model cyanobacterial Synechocystis sp. PCC 6803 to ethanol were determined using a quantitative proteomics approach with iTRAQ LC-MS/MS technologies. The resulting high-quality proteomic data set consisted of 24,887 unique peptides corresponding to 1509 identified proteins, a coverage of approximately 42% of the predicted proteins in the Synechocystis genome. Using a cutoff of 1.5-fold change and a p-value less than 0.05, 135 and 293 unique proteins with differential abundance levels were identified between control and ethanol-treated samples at 24 and 48 h, respectively. Functional analysis showed that the Synechocystis cells employed a combination of induced common stress response, modifications of cell membrane and envelope, and induction of multiple transporters and cell mobility-related proteins as protection mechanisms against ethanol toxicity. Interestingly, our proteomic analysis revealed that proteins related to multiple aspects of photosynthesis were up-regulated in the ethanol-treated Synechocystis cells, consistent with increased chlorophyll a concentration in the cells upon ethanol exposure. The study provided the first comprehensive view of the complicated molecular mechanisms against ethanol stress and also provided a list of potential gene targets for further engineering ethanol tolerance in Synechocystis PCC 6803.