Affordable oral health care: dental biofilm disruption using chloroplast made enzymes with chewing gum delivery.

Current approaches for oral health care rely on procedures that are unaffordable to impoverished populations, whereas aerosolized droplets in the dental clinic and poor oral hygiene may contribute to spread of several infectious diseases including COVID-19, requiring new solutions for dental biofilm/plaque treatment at home. Plant cells have been used to produce monoclonal antibodies or antimicrobial peptides for topical applications to decrease colonization of pathogenic microbes on dental surface. Therefore, we investigated an affordable method for dental biofilm disruption by expressing lipase, dextranase or mutanase in plant cells via the chloroplast genome. Antibiotic resistance gene used to engineer foreign genes into the chloroplast genome were subsequently removed using direct repeats flanking the aadA gene and enzymes were successfully expressed in marker-free lettuce transplastomic lines. Equivalent enzyme units of plant-derived lipase performed better than purified commercial enzymes against biofilms, specifically targeting fungal hyphae formation. Combination of lipase with dextranase and mutanase suppressed biofilm development by degrading the biofilm matrix, with concomitant reduction of bacterial and fungal accumulation. In chewing gum tablets formulated with freeze-dried plant cells, expressed protein was stable up to 3 years at ambient temperature and was efficiently released in a time-dependent manner using a mechanical chewing simulator device. Development of edible plant cells expressing enzymes eliminates the need for purification and cold-chain transportation, providing a potential translatable therapeutic approach. Biofilm disruption through plant enzymes and chewing gum-based delivery offers an effective and affordable dental biofilm control at home particularly for populations with minimal oral care access.

Extraction and Detection of Structurally Diverse Siderophores in Soil.

Although the biochemistry of bacterial and fungal siderophores has been intensively studied in laboratory cultures, their distribution and impacts on nutrient cycling and microbial communities in soils remain poorly understood. The detection of siderophores in soil is an analytical challenge because of the complexity of the soil matrix and their structural diversity. Liquid chromatography-mass spectrometry (LC-MS) is a suitable method for the sensitive analysis of siderophores in complex samples; however, siderophore extraction into liquid phases for analysis by LC-MS is problematic because of their adsorption to soil particles and organic matter. To determine extraction efficiencies of structurally diverse siderophores, spike-recovery experiments were set up with standards representing the three main siderophore classes: the hydroxamate desferrioxamine B (DFOB), the α-hydroxycarboxylate rhizoferrin, and the catecholate protochelin. Previously used solvent extractions with water or methanol recovered only a small fraction (< 35%) of siderophores, including < 5% for rhizoferrin and protochelin. We designed combinatorial chemical extractions (22 total solutions) to target siderophores associated with different soil components. A combination of calcium chloride and ascorbate achieved high and, for some soils, quantitative extraction of DFOB and rhizoferrin. Protochelin analysis was complicated by potential fast oxidation and interactions with colloidal soil components. Using the optimized extraction method, we detected α-hydroxycarboxylate type siderophores (viz. rhizoferrin, vibrioferrin, and aerobactin) in soil for the first time. Concentrations reached 461 pmol g-1, exceeding previously reported concentrations of siderophores in soil and suggesting a yet unrecognized importance of α-hydroxycarboxylate siderophores for biological interactions and biogeochemical processes in soil.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology.

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

Untargeted Metabolomics Workshop Report: Quality Control Considerations from Sample Preparation to Data Analysis.

The Proteomics Society, India (PSI), hosted the Metabolomics workshop on experimental and data analysis training for untargeted metabolomics in December 2019. The workshop included six tutorial lectures and hands-on data analysis training sessions presented by seven speakers from across the globe. The tutorials and hands-on data analysis sessions focused on workflows for liquid chromatography-mass spectrometry (LC-MS) based on untargeted metabolomics. We review here three main topics from the workshop, which were uniquely identified as bottlenecks for new researchers: (a) experimental design, (b) quality controls during sample preparation and instrumental analysis, and (c) data quality evaluation using open source tools. Our objective here is to present common challenges faced by novice researchers and present guidelines to address them. We provide resources and good practices for researchers who are at the initial stage of setting up metabolomics workflows in their laboratories.

Immune Dysfunction and Multiple Treatment Modalities for the SARS-CoV-2 Pandemic: Races of Uncontrolled Running Sweat?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic threat with more than 11.8 million confirmed cases and more than 0.5 million deaths as of 3 July 2020. Given the lack of definitive pharmaceutical interventions against SARS-CoV-2, multiple therapeutic strategies and personal protective applications are being used to reduce the risk of high mortality and community spread of this infection. Currently, more than a hundred vaccines and/or alternative therapeutic regimens are in clinical trials, and some of them have shown promising results in improving the immune cell environment and controlling the infection. In this review, we discussed high-performance multi-directory strategies describing the uncontrolled deregulation of the host immune landscape associated with coronavirus disease (COVID-19) and treatment strategies using an anti-neoplastic regimen. We also followed selected current treatment plans and the most important on-going clinical trials and their respective outcomes for blocking SARS-CoV-2 pathogenesis through regenerative medicine, such as stem cell therapy, chimeric antigen receptors, natural killer (NK) cells, extracellular vesicular-based therapy, and others including immunomodulatory regimens, anti-neoplastic therapy, and current clinical vaccine therapy.

Cold chain and virus-free oral polio booster vaccine made in lettuce chloroplasts confers protection against all three poliovirus serotypes.

To prevent vaccine-associated paralytic poliomyelitis, WHO recommended withdrawal of Oral Polio Vaccine (Serotype-2) and a single dose of Inactivated Poliovirus Vaccine (IPV). IPV however is expensive, requires cold chain, injections and offers limited intestinal mucosal immunity, essential to prevent polio reinfection in countries with open sewer system. To date, there is no virus-free and cold chain-free polio vaccine capable of inducing robust mucosal immunity. We report here a novel low-cost, cold chain/poliovirus-free, booster vaccine using poliovirus capsid protein (VP1, conserved in all serotypes) fused with cholera non-toxic B subunit (CTB) expressed in lettuce chloroplasts. PCR using unique primer sets confirmed site-specific integration of CTB-VP1 transgene cassettes. Absence of the native chloroplast genome in Southern blots confirmed homoplasmy. Codon optimization of the VP1 coding sequence enhanced its expression 9-15-fold in chloroplasts. GM1-ganglioside receptor-binding ELISA confirmed pentamer assembly of CTB-VP1 fusion protein, fulfilling a key requirement for oral antigen delivery through gut epithelium. Transmission Electron Microscope images and hydrodynamic radius analysis confirmed VP1-VLPs of 22.3 nm size. Mice primed with IPV and boosted three times with lyophilized plant cells expressing CTB-VP1co, formulated with plant-derived oral adjuvants, enhanced VP1-specific IgG1, VP1-IgA titres and neutralization (80%-100% seropositivity of Sabin-1, 2, 3). In contrast, IPV single dose resulted in <50% VP1-IgG1 and negligible VP1-IgA titres, poor neutralization and seropositivity (<20%, <40% Sabin 1,2). Mice orally boosted with CTB-VP1co, without IPV priming, failed to produce any protective neutralizing antibody. Because global population is receiving IPV single dose, booster vaccine free of poliovirus or cold chain offers a timely low-cost solution to eradicate polio.

Time for Multiple Extraction Methods in Proteomics? A Comparison of Three Protein Extraction Methods in the Eustigmatophyte Alga Microchloropsis gaditana CCMP526.

Proteomics is a crucial postgenomic biotechnology for functional and systems scale analyses in cell and integrative biology, not to mention clinical and precision medicine research. However, a fundamental requirement for an accurate examination of the protein complement of cells is an efficient method for extracting the proteins. This study reports on the evaluation of three protein extraction methods: trichloroacetic acid (TCA)-acetone, phenol, and TRIzol, in the eustigmatophyte alga Microchloropsis gaditana CCMP526 for proteomic analysis. M. gaditana is a potential candidate for algal-based biofuels. This industrially important strain is also rich in dietary oil and pigments and is used as feed in the aquaculture industry. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analysis was performed for proteins obtained using the three extraction methods and their effects were examined by the abundance ratio. Protein yield was higher using the TCA-acetone and phenol methods than with the TRIzol method. The TCA method was superior than other methods examined here in terms of protein coverage and abundance. Subcellular localization of the identified proteins revealed no significant difference among the extraction methods. Importantly, each method revealed a unique set of proteins. To the best of our knowledge, this is the first report on evaluation of protein extraction methods for the proteomic analysis of M. gaditana CCMP526. These observations underscore the importance of using multiple protein extraction methods for comprehensive proteome coverage, as the field of proteomics edges toward diverse applications in biofuels, aquaculture industry, marine biology, and agriculture.

Real-time iTRAQ-based proteome profiling revealed the central metabolism involved in nitrogen starvation induced lipid accumulation in microalgae.

To understand the post-transcriptional molecular mechanisms attributing to oleaginousness in microalgae challenged with nitrogen starvation (N-starvation), the longitudinal proteome dynamics of Chlorella sp. FC2 IITG was investigated using multipronged quantitative proteomics and multiple reaction monitoring assays. Physiological data suggested a remarkably enhanced lipid accumulation with concomitant reduction in carbon flux towards carbohydrate, protein and chlorophyll biosynthesis. The proteomics-based investigations identified the down-regulation of enzymes involved in chlorophyll biosynthesis (porphobilinogen deaminase) and photosynthetic carbon fixation (sedoheptulose-1,7 bisphosphate and phosphoribulokinase). Profound up-regulation of hydroxyacyl-ACP dehydrogenase and enoyl-ACP reductase ascertained lipid accumulation. The carbon skeletons to be integrated into lipid precursors were regenerated by glycolysis, ß-oxidation and TCA cycle. The enhanced expression of glycolysis and pentose phosphate pathway enzymes indicates heightened energy needs of FC2 cells for the sustenance of N-starvation. FC2 cells strategically reserved nitrogen by incorporating it into the TCA-cycle intermediates to form amino acids; particularly the enzymes involved in the biosynthesis of glutamate, aspartate and arginine were up-regulated. Regulation of arginine, superoxide dismutase, thioredoxin-peroxiredoxin, lipocalin, serine-hydroxymethyltransferase, cysteine synthase, and octanoyltransferase play a critical role in maintaining cellular homeostasis during N-starvation. These findings may provide a rationale for genetic engineering of microalgae, which may enable synchronized biomass and lipid synthesis.

Multi-omics Frontiers in Algal Research: Techniques and Progress to Explore Biofuels in the Postgenomics World.

Current momentum of microalgal research rests extensively in tapping the potential of multi-omics methodologies in regard to sustainable biofuels. Microalgal biomass is fermented to bioethanol; while lipids, particularly triacylglycerides (TAGs), are transesterified to biodiesels. Biodiesel has emerged as an ideal biofuel candidate; hence, its commercialization and use are increasingly being emphasized. Abiotic stresses exaggerate TAG accumulation, but the precise mechanisms are yet to be known. More recently, comprehensive multi-omics studies in microalgae have emerged from the biofuel perspective. Genomics and transcriptomics of microalgae have provided crucial leads and basic understanding toward lipid biosynthesis. Proteomics and metabolomics are now complementing "algal omics" and offer precise functional insights into the attendant static and dynamic physiological contexts. Indeed, the field has progressed from shotgun to targeted approaches. Notably, targeted proteomics studies in microalga are not yet reported. Several multi-omics tools and technologies that may be used to dig deeper into the microalgal physiology are examined and highlighted in this review. The article therefore aims to both introduce various available high-throughput biotechnologies and applications of "omics" in microalgae, and enlists a compendium of the emerging cutting edge literature. We suggest that a strategic and thoughtful combination of data streams from different omics platforms can provide a system-wide overview. The algal omics warrants closer attention in the future, with a view to technical, economic, and societal impacts that are anticipated in the current postgenomics era.

Overexpression of human peroxisomal enoyl-CoA delta isomerase2 HsPECI2, an ortholog of bamboo expressed during gregarious flowering alters salinity stress responses and polar lipid content in tobacco.

Peroxisomal enoyl-CoA delta isomerase2 (PECI2) is one of the key enzymes that has critical role in lipid metabolism and plant development during salt stress. Seven out of ten tobacco plants overexpressing human PECI2 (HsPECI2) with PTS1-sequence showed hypersensitivity to salt. Under salt-stress, T2 transformed plants (HsPECI2) displayed reduced primary root, delayed shoot-growth, and visibly smaller rosette leaves turning pale yellow as compared to the pKYLX71 vector control plant. Also, we found altered reactive oxygen species (ROS) levels and reduced catalase activity in 100mM sodium chloride (NaCl) treated HsPECI2 transformed plant compared with the pKYLX71 counterpart. ESI-MS/MS data showed that the polar lipids were differentially modulated upon salt treatment in HsPECI2 transformed and pKYLX71 plants as compared with the respective untreated counterpart. Notably, the levels of monogalactosyldiacylglycerol and phosphatidic acid varied significantly, whereas phosphatidylcholine, phosphatidylserine and digalactosyldiacylglycerol contents were moderately upregulated. In parallel, abscisic acid (ABA) responsiveness assay confirmed insensitivity of HsPECI2 transformed plant towards ABA. Overall our data proclaim that HsPECI2 play multifunctional role in normal development and response to salinity stress apart from its primary role in ß-oxidation.