Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets

Aging is closely related to the occurrence of human diseases; however, its exact biological mechanism is unclear. Advancements in high-throughput technology provide new opportunities for omics research to understand the pathological process of various complex human diseases. However, single-omics technologies only provide limited insights into the biological mechanisms of diseases. DNA, RNA, protein, metabolites, and microorganisms usually play complementary roles and perform certain biological functions together. In this review, we summarize multi-omics methods based on the most relevant biomarkers in single-omics to better understand molecular functions and disease causes. The integration of multi-omics technologies can systematically reveal the interactions among aging molecules from a multidimensional perspective. Our review provides new insights regarding the discovery of aging biomarkers, mechanism of aging, and identification of novel antiaging targets. Overall, data from genomics, transcriptomics, proteomics, metabolomics, integromics, microbiomics, and systems biology contribute to the identification of new candidate biomarkers for aging and novel targets for antiaging interventions.

Public Health Genomics – Treading Two Parallel Tracks

Against the backdrop of a decrepit healthcare system, where health for all is still a ‘distant’ dream, exposing stark gaps and shortfall of crucial inputs at various levels in catering to the health needs and requirements of a large population has compelled a review of the existing system and innovative course corrections. It has invoked a functional vision based on two parallel tracks; one, to rejuvenate and efficiently manage existing healthcare infrastructure and associated healthcare professionals at the village, tehsil and district level; and, the other of providing the modern facilities of diagnosis, prognosis, and preventive investigations with requisite interventions across all sections of the society. For more precise interventions to advance health the proposed two-pronged approach would ensure and safeguard the health, and inter alia reduce morbidity and mortality. Precision medicine in public health is predicated on OMICS technologies along with big data, machine learning and artificial intelligence for disease risk predictions and management in future. The capital intensive character of such technologies does raise concerns about their affordability, demanding an inter-institutional effort to generate simple and cost-effective high-throughput technology and tools for the diagnosis of diseases. The necessity to adopt modern medical biology technologies including Genomics has been amply evident in the COVID-19 pandemic through variant characterization of SARS-CoV2, and anticipated variations in the human host for differential susceptibilities and outcome of the disease.

Intercomparison of Two Fluorescent Dyes to Visualize Parasitic Fungi (Chytridiomycota) on Phytoplankton

Fungal microparasites (here chytrids) are widely distributed and yet, they are often overlooked in aquatic environments. To facilitate the detection of microparasites, we revisited the applicability of two fungal cell wall markers, Calcofluor White (CFW) and wheat germ agglutinin (WGA), for the direct visualization of chytrid infections on phytoplankton in laboratory-maintained isolates and field-sampled communities. Using a comprehensive set of chytrid–phytoplankton model pathosystems, we verified the staining pattern on diverse morphological structures of chytrids via fluorescence microscopy. Empty sporangia were stained most effectively, followed by encysted zoospores and im-/mature sporangia, while the staining success was more variable for rhizoids, stalks, and resting spores. In a few instances, the staining was unsuccessful (mostly with WGA), presumably due to insufficient cell fixation, gelatinous cell coatings, and multilayered cell walls. CFW and WGA staining could be done in Utermöhl chambers or on polycarbonate filters, but CFW staining on filters seemed less advisable due to high background fluorescence. To visualize chytrids, 1 µg dye mL−1 was sufficient (but 5 µg mL−1 are recommended). Using a dual CFW–WGA staining protocol, we detected multiple, mostly undescribed chytrids in two natural systems (freshwater and coastal), while falsely positive or negative stained cells were well detectable. As a proof-of-concept, we moreover conducted imaging flow cytometry, as a potential high-throughput technology for quantifying chytrid infections. Our guidelines and recommendations are expected to facilitate the detection of chytrid epidemics and to unveil their ecological and economical imprint in natural and engineered aquatic systems.

Caloric Restriction Mimetics Attenuate the Hallmarks of Aging

Nutrient depletion, which is one of the physiological triggers of autophagy, results in the depletion of intracellular acetyl coenzyme A (AcCoA) coupled to the deacetylation of cellular proteins. We found that there are at least 4 possibilities to mimic these effects, namely (i) the depletion of cytosolic AcCoA by interfering with its biosynthesis, (ii) the stimulation cytosolic AcCoA consumption, (iii) the inhibition of protein acetyltransferases, or (iii) the stimulation of protein deacetylases. Thus, AcCoA depleting agents, AcCoA-consuming agents, acetyltransferase inhibitors or deacetylase activators are highly efficient inducers of autophagy and reduce aging-associated diseases including diabetes, obesity, cardiac failure and failing cancer immunosurveillance. Hence, we classify them as “caloric restriction mimetics” (CRM). We have initiated the systematic search for CRMs based on their cellular effects in vitro. We built screening assays amenable to high-throughput technology for the identification of CRMs. These results will be discussed.

Self-Assembled Ag Nanocomposites into Ultra-Sensitive and Reproducible Large-Area SERS-Active Opaque Substrates

This work describes a novel, one-shot strategy to fabricate ultrasensitive SERS sensors based on silver/poly(methyl methacrylate) (PMMA) nanocomposites. Upon spin coating of a dispersion of PMMA and silver precursor on N-doped silicon substrate, closely separated silver nanoparticles were self-assembled into uniform nanospheres. As a result, a thin hydrophobic PMMA layer embedded with Ag nanoparticles (AgNPs) was obtained on the whole silicon substrate. Consequently, a large-scale, reproducible SERS platform was produced through a rapid, simple, low-cost, and high-throughput technology. In addition, reproducible SERS features and high SERS enhancement factors were determined (SEF ~1015). This finding matches the highest SEF reported in literature to date (1014) for silver aggregates. The potential and novelty of this synthesis is that no reducing agent or copolymer was used, nor was any preliminary functionalization of the surface carried out. In addition, the AgNPs were fabricated directly on the substrate’s surface; consequently, there was no need for polymer etching. Then, the synthetic method was successfully applied to prepare opaque SERS platforms. Opaque surfaces are needed in photonic devices because of the absence of secondary back reflection, which makes optical analysis and applications easier.

Advancement of antigen-specific immunotherapy: knowledge transfer between allergy and autoimmunity

Targeted restoration of immunological tolerance to self-antigens or innocuous environmental allergens represents the ultimate aim of treatment options in autoimmune and allergic disease. Antigen-specific immunotherapy (ASI) is the only intervention that has proven disease-modifying efficacy as evidenced by induction of long-term remission in a number of allergic conditions. Mounting evidence is now indicating that specific targeting of pathogenic T cells in autoinflammatory and autoimmune settings enables effective restoration of immune homeostasis between effector and regulatory cells and alters the immunological course of disease.Here we discuss the key lessons learned during the development of antigen-specific immunotherapies and how these can be applied to inform future interventions. Armed with this knowledge and current high-throughput technology to track immune cell phenotype and function, it may no longer be a matter of ‘if’ but ‘when’ this ultimate aim of targeted tolerance restoration is realised.

Replicating Light-Off Startle Responses in Drosophila melanogaster

We present a highly reproducible method for investigating the startle flight responses of wild type Drosophila melanogaster to light-off stimuli, using the automated Zantiks MWP unit. The built-in, live video-tracking of the Zantiks unit measured distance travelled between frames for 24 flies after light-off stimuli, whilst providing video-recordings of each startle. Using light-off stimuli which elicited peak startling, we found evidence for habituation of the startle response after only a few consecutive trials. Distance travelled on startle trials was reduced when a prepulse stimulus of shorter duration was introduced before the light-off stimulus, providing behavioural evidence for prepulse inhibition (PPI). Deficits in habituation and PPI are linked to various psychiatric disorders and our method holds great potential for use alongside genetic and pharmacological manipulations. Here, we demonstrate the capability of this highly automated, high throughput technology to streamline behavioural research on Drosophila, using a replicable, controlled environment.

Integrating microbiome, transcriptome and metabolome data to investigate gastric disease pathogenesis: a concise review

Microbiome, the study of microbial communities in specific environments, has developed significantly since the Human Microbiome Project began. Microbiomes have been associated with changes within environmental niches and the development of various diseases. The development of high-throughput technology such as next-generation sequencing has also allowed us to perform transcriptome studies, which provide accurate functional profiling data. Metabolome studies, which analyse the metabolites found in the environment, are the most direct environmental condition indicator. Although each dataset provides valuable information on its own, the integration of multiple datasets provides a deeper understanding of the relationship between the host, agent and environment. Therefore, network analysis using multiple datasets might give a clearer understanding of disease pathogenesis.