Tecoma stans Floral Extract-Based Biosynthesis for Enhanced Surface Plasmon-Coupled Emission and a Preliminary Study on Fluoroimmunoassay

We demonstrate the synthesis of biogenic supported silver spiked star architectures and their application to increase the electromagnetic field intensity at its tips that enhance plasmon-coupled emission. Tecoma stans floral extract has been used to synthesize silver nanocubes and spiked stars. We observe ∼445-fold and ∼680-fold enhancements in spacer and cavity configurations, respectively, in the SPCE platform. The hotspot intensity and Purcell factor are evaluated by carrying out finite-difference time-domain (FDTD) simulations. Time-based studies are presented to modulate the sharpness of the edges wherein an increase in the tip sharpness with the increase in reaction time up to 5 h is observed. The unique morphology of the silver architectures allowed us to utilize them in biosensing application. A SPCE-based fluoroimmunoassay was performed, achieving a 1.9 pg/mL limit of detection of TNF-α cytokine. This combination of anisotropic architectures, SPCE and immunoassay prove to be a powerful platform for the ultrasensitive detection of biomarkers in surface-bound assays.

Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease

PURPOSE

Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases.

METHODS

The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature.

RESULTS

The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

Integrated Omic Analysis Delineates Pathways Modulating Toxic TDP-43 Protein Aggregates in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a multi-systemic, incurable, amyloid disease affecting the motor neurons, resulting in the death of patients. The disease is either sporadic or familial with SOD1, C9orf72, FUS, and TDP-43 constituting the majority of familial ALS. Multi-omics studies on patients and model systems like mice and yeast have helped in understanding the association of various signaling and metabolic pathways with the disease. The yeast model system has played a pivotal role in elucidating the gene amyloid interactions. We carried out an integrated transcriptomic and metabolomic analysis of the TDP-43 expressing yeast model to elucidate deregulated pathways associated with the disease. The analysis shows the deregulation of the TCA cycle, single carbon metabolism, glutathione metabolism, and fatty acid metabolism. Transcriptomic analysis of GEO datasets of TDP-43 expressing motor neurons from mice models of ALS and ALS patients shows considerable overlap with experimental results. Furthermore, a yeast model was used to validate the obtained results using metabolite addition and gene knock-out experiments. Taken together, our result shows a potential role for the TCA cycle, cellular redox pathway, NAD metabolism, and fatty acid metabolism in disease. Supplementation of reduced glutathione, nicotinate, and the keto diet might help to manage the disease.

Integrated multi-omics analysis of Huntington disease identifies pathways that modulate protein aggregation

Huntington disease (HD) is a neurodegenerative disease associated with polyglutamine expansion in the protein huntingtin (HTT). Although the length of the polyglutamine repeat correlates with age at disease onset and severity, psychological, cognitive and behavioral complications point to the existence of disease modifiers. Mitochondrial dysfunction and metabolic deregulation are both associated with the HD but, despite multi-omics characterization of patients and model systems, their mechanisms have remained elusive. Systems analysis of multi-omics data and its validation by using a yeast model could help to elucidate pathways that modulate protein aggregation. Metabolomics analysis of HD patients and of a yeast model of HD was, therefore, carried out. Our analysis showed a considerable overlap of deregulated metabolic pathways. Further, the multi-omics analysis showed deregulated pathways common in human, mice and yeast model systems, and those that are unique to them. The deregulated pathways include metabolic pathways of various amino acids, glutathione metabolism, longevity, autophagy and mitophagy. The addition of certain metabolites as well as gene knockouts targeting the deregulated metabolic and autophagy pathways in the yeast model system showed that these pathways do modulate protein aggregation. Taken together, our results showed that the modulation of deregulated pathways influences protein aggregation in HD, and has implications for progression and prognosis. This article has an associated First Person interview with the first author of the paper.