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Friedreich’s ataxia, an autosomal recessive disorder, is caused by tandem GAA nucleotide repeat expansions in intron 1 of the frataxin gene. The GAA repeats over 66 in number are considered as pathogenic, and commonly occurring pathogenic repeats are within a range of 600–1200. Clinically, the spectrum of features is confined mainly to neurological tissues; however, cardiomyopathy and diabetes mellitus have been reported in 60 and 30% of the subjects, respectively. The accurate detection of GAA repeat count is of utmost importance for clinical genetic correlation, and no study so far has attempted an approach that is of high-throughput nature and defines the exact sequence of GAA repeats. Largely, the method for detection of GAA repeats so far is either through the conventional polymerase chain reaction-based screening or Southern blot, which remains the gold standard method. We utilized an approach of long-range targeted amplification of FXN-GAA repeats using Oxford Nanopore Technologies MinION platform for accurate estimation of repeat length. We were able to achieve successful amplification of GAA repeats ranging from ∼120 to 1100 at ∼2600× mean coverage. The total throughput achievable through our protocol can allow for screening of up to 96 samples per flow cell in less than 24 h. The proposed method is clinically scalable and deployable for day-to-day diagnostics. In this paper, we demonstrate to resolve the genotype–phenotype correlation of Friedreich’s ataxia patients with better accuracy.

IntroductionDespite numerous efforts to describe COVID-19's immunological landscape, there is still a gap in our understanding of the virus's infections after-effects, especially in the recovered patients. This would be important to understand as we now have huge number of global populations infected by the SARS-CoV-2 as well as variables inclusive of VOCs, reinfections, and vaccination breakthroughs. Furthermore, single-cell transcriptome alone is often insufficient to understand the complex human host immune landscape underlying differential disease severity and clinical outcome.MethodsBy combining single-cell multi-omics (Whole Transcriptome Analysis plus Antibody-seq) and machine learning-based analysis, we aim to better understand the functional aspects of cellular and immunological heterogeneity in the COVID-19 positive, recovered and the healthy individuals.ResultsBased on single-cell transcriptome and surface marker study of 163,197 cells (124,726 cells after data QC) from the 33 individuals (healthy=4, COVID-19 positive=16, and COVID-19 recovered=13), we observed a reduced MHC Class-I-mediated antigen presentation and dysregulated MHC Class-II-mediated antigen presentation in the COVID-19 patients, with restoration of the process in the recovered individuals. B-cell maturation process was also impaired in the positive and the recovered individuals. Importantly, we discovered that a subset of the naive T-cells from the healthy individuals were absent from the recovered individuals, suggesting a post-infection inflammatory stage. Both COVID-19 positive patients and the recovered individuals exhibited a CD40-CD40LG-mediated inflammatory response in the monocytes and T-cell subsets. T-cells, NK-cells, and monocyte-mediated elevation of immunological, stress and antiviral responses were also seen in the COVID-19 positive and the recovered individuals, along with an abnormal T-cell activation, inflammatory response, and faster cellular transition of T cell subtypes in the COVID-19 patients. Importantly, above immune findings were used for a Bayesian network model, which significantly revealed FOS, CXCL8, IL1β, CST3, PSAP, CD45 and CD74 as COVID-19 severity predictors.DiscussionIn conclusion, COVID-19 recovered individuals exhibited a hyper-activated inflammatory response with the loss of B cell maturation, suggesting an impeded post-infection stage, necessitating further research to delineate the dynamic immune response associated with the COVID-19. To our knowledge this is first multi-omic study trying to understand the differential and dynamic immune response underlying the sample subtypes.

The modulators of severe COVID-19 have emerged as the most intriguing features of SARS-CoV-2 pathogenesis. This is especially true as we are encountering variants of concern (VOC) with increased transmissibility and vaccination breakthroughs. Microbial co-infections are being investigated as one of the crucial factors for exacerbation of disease severity and complications of COVID-19. A key question remains whether early transcriptionally active microbial signature/s in COVID-19 patients can provide a window for future disease severity susceptibility and outcome? Using complementary metagenomics sequencing approaches, respiratory virus oligo panel (RVOP) and Holo-seq, our study highlights the possible functional role of nasopharyngeal early resident transcriptionally active microbes in modulating disease severity, within recovered patients with sub-phenotypes (mild, moderate, severe) and mortality. The integrative analysis combines patients' clinical parameters, SARS-CoV-2 phylogenetic analysis, microbial differential composition, and their functional role. The clinical sub-phenotypes analysis led to the identification of transcriptionally active bacterial species associated with disease severity. We found significant transcript abundance of Achromobacter xylosoxidans and Bacillus cereus in the mortality, Leptotrichia buccalis in the severe, Veillonella parvula in the moderate, and Actinomyces meyeri and

Along with the evolutionary breakthrough of RNA interference and the applicability for gene knockdown, a subsequent development in siRNA-based therapeutics has been attained. The gene therapy based on RNAi is in transition progress from the research aspects to clinical base. Being a potent tool, siRNA is used as therapeutic against several disorders. Cancer which is one of the deadliest diseases is now treated with an advanced mechanism of siRNA delivery inside the genome, leading to gene silencing; thereby, blocking translation of gene to form protein. siRNA tool delivers remedial effects with the advantages of safe delivery and efficiency. Despite its merits, barriers including instability at physiological conditions, lack of ability to cross biological membranes, off-targets, and safety are also associated with siRNA delivery system. The gene silencing efficiency values both in vitro and in vivo reported in the past years have been reviewed by material type (lipid, polymer, silica, porous silicon, and metal). This review presents a deep insight in the development of targeted delivery of siRNA. Since several clinical trials have also been performed regarding the siRNA delivery against cancer, it can also be stated that the delivery system should be good enough to achieve effective siRNA drug development.

Friedreich ataxia, an autosomal recessive disorder is caused by tandem GAA nucleotide repeats expansion in intron 1 of the FXN (frataxin gene). The GAA repeats above 66 in length are considered as pathogenic and commonly occurring repeats are 600-1200. Clinically the spectrum of the features is confined mainly to the neurological tissue, however, cardiomyopathy and diabetes mellitus has been observed in 60% and 30% of the subjects. The accurate detection of GAA repeats count is of utmost importance for clinical genetic correlation as no study has attempted an approach which is of high throughput nature and defines the sequence of GAA repeats. Largely, the method for detection of GAA repeats so far is either conventional PCR based screening and southern blot which is the gold standard method. We describe for the first time a method of long read sequencing wherein we utilized approach of long range targeted amplification of FXN-GAA repeats and sequencing on oxford MinION platform. We were able to achieve the successful amplification of GAA repeats ranging from 180-1200 at 250x coverage. The total throughput achievable for 96 samples can be less than 24 hours on one flow cell as per our protocol and is scalable and deployable at clinical day to sequencing.

Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host–pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.

Disease caused by SARS-CoV-2 coronavirus (COVID-19) led to significant morbidity and mortality worldwide. A systemic hyper-inflammation characterizes severe COVID-19 disease, often associated with acute respiratory distress syndrome (ARDS). Blood biomarkers capable of risk stratification are of great importance in effective triage and critical care of severe COVID-19 patients. Flow cytometry and next-generation sequencing were done on peripheral blood cells and urokinase-type plasminogen activator receptor (suPAR), and cytokines were measured from and mass spectrometry-based proteomics was done on plasma samples from an Indian cohort of COVID-19 patients. Publicly available single-cell RNA sequencing data were analyzed for validation of primary data. Statistical analyses were performed to validate risk stratification. We report here higher plasma abundance of suPAR, expressed by an abnormally expanded myeloid cell population, in severe COVID-19 patients with ARDS. The plasma suPAR level was found to be linked to a characteristic plasma proteome, associated with coagulation disorders and complement activation. Receiver operator characteristic curve analysis to predict mortality identified a cutoff value of suPAR at 1,996.809 pg/ml (odds ratio: 2.9286, 95% confidence interval 1.0427–8.2257). Lower-than-cutoff suPAR levels were associated with a differential expression of the immune transcriptome as well as favorable clinical outcomes, in terms of both survival benefit (hazard ratio: 0.3615, 95% confidence interval 0.1433–0.912) and faster disease remission in our patient cohort. Thus, we identified suPAR as a key pathogenic circulating molecule linking systemic hyperinflammation to the hypercoagulable state and stratifying clinical outcomes in severe COVID-19 patients with ARDS.

Human host and pathogen interaction is dynamic in nature and often modulated by co-pathogens with a functional role in delineating the physiological outcome of infection. Co-infection may present either as a pre-existing pathogen which is accentuated by the introduction of a new pathogen or may appear in the form of new infection acquired secondarily due to a compromised immune system. Using diverse examples of co-infecting pathogens such as Human Immunodeficiency Virus,Mycobacterium tuberculosisand Hepatitis C Virus, we have highlighted the role of co-infections in modulating disease severity and clinical outcome. This interaction happens at multiple hierarchies, which are inclusive of stress and immunological responses and together modulate the disease severity. Already published literature provides much evidence in favor of the occurrence of co-infections during SARS-CoV-2 infection, which eventually impacts the Coronavirus disease-19 outcome. The availability of biological models like 3D organoids, mice, cell lines and mathematical models provide us with an opportunity to understand the role and mechanism of specific co-infections. Exploration of multi-omics-based interactions across co-infecting pathogens may provide deeper insights into their role in disease modulation.

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

The communicable Hepatitis C Virus (HCV) infection causes global health problems and deaths due to transmission by blood and body fluids and general symptoms include loss of appetite, fatigue, fever, abdominal pain, swelling, jaundice, and dark urine.This study contains a detailed study about the potent biochemical biomarkers for the diagnosis and detection of HCV infection. It includes the biochemical profiling relating to the HCV infection among both the genders of the human population is included in this paper.96 (5ml) EDTA blood samples of suspected HCV infected patients were collected from the different hospitals in Dehradun, Uttarakhand, India. The RNA extraction was performedwith the help of QIAamp Viral RNA mini kit (Cat. no. 52904). The HCV RNA quantification was achieved using the machine named Rotor Gene Q5 Plex Real-Time PCR and master mix was prepared by the Artus Amplification Kit from Qiagen.Out of 96 samples collected for HCV RNA biochemical profiling, 58 cases i.e., were found with the heavy load of virus and the study had 38 cases in which target virus was not detected. The biochemical investigation was performed on 96 cases with a high viral load of more than 34 IU/ml (≥34 IU/ml). The cases belonging to age 21-40 and 41-60 years were found to be most prominent among 35 and 37 cases respectively due to the repeated exposure to infected blood and the age group of 0-20 years was found to be least susceptible due to the protective antibody titer against HCV due to the vaccination in early age.

Cerebellar ataxias (CAs) represent a group of autosomal dominant and recessive neurodegenerative disorders affecting cerebellum with or without spinal cord. Overall, CAs have preponderance for tandem nucleotide repeat expansions as an etiological factor (10 TREs explain nearly 30-40% of ataxia cohort globally). The experience of 10 years of common genetic ataxia subtypes for ≈5600 patients' referrals (Pan-India) received at a single center is shared herein. Frequencies (in %, n) of SCA types and FRDA in the sample cohort are observed as follows: SCA12 (8.6%, 490); SCA2 (8.5%, 482); SCA1 (4.8%, 272); SCA3 (2%, 113); SCA7 (0.5%, 28); SCA6 (0.1%, 05); SCA17 (0.1%, 05), and FRDA (2.2%, 127). A significant amount of variability in TRE lengths at each locus is observed, we noted presence of biallelic expansion, co-occurrence of SCA-subtypes, and the presence of premutable normal alleles. The frequency of mutated GAA-FRDA allele in healthy controls is 1/158 (0.63%), thus an expected FRDA prevalence of 1:100 000 persons. The data of this study are relevant not only for clinical decision making but also for guidance in direction of genetic investigations, transancestral comparison of genotypes, and lastly provide insight for policy decision for the consideration of SCAs under rare disease category.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged the research community globally to innovate, interact, and integrate findings across hierarchies. Research on SARS-CoV-2 has produced an abundance of data spanning multiple parallels, including clinical data, SARS-CoV-2 genome architecture, host response captured through transcriptome and genetic variants, microbial co-infections (metagenome), and comorbidities. Disease phenotypes in the case of COVID-19 present an intriguing complexity that includes a broad range of symptomatic to asymptomatic individuals, further compounded by a vast heterogeneity within the spectrum of clinical symptoms displayed by the symptomatic individuals. The clinical outcome is further modulated by the presence of comorbid conditions at the point of infection. The COVID-19 pandemic has produced an expansive wealth of literature touching many aspects of SARS-CoV-2 ranging from causal to outcome, predisposition to protective (possible), co-infection to comorbidity, and differential mortality globally. As challenges provide opportunities, the current pandemic’s challenge has underscored the need and opportunity to work for an integrative approach that may be able to thread together the multiple variables. Through this review, we have made an effort towards bringing together information spanning across different domains to facilitate researchers globally in pursuit of their response to SARS-CoV-2.

RNA are integral to stress response which by nature require immediate and modular response. Non-coding RNA, a subset of the transcriptome, are integral to stress response. Literature highlights the specific role played by diverse array of ncRNAs during the spectrum of biotic and abiotic stress conditions. These ncRNAs display a spatio-temporal pattern which are important for physiological homeostasis. Given the whole gamut of causal, association and prognostic role of ncRNAs, future potential in therapeutic usage does not seem to be far away.

Background Alcohol dependence (AD), characterized by profound disruptions in specific circuits of the brain is influenced by both environmental, which play a significant role in developing addiction and genetic factors, which make some individuals more susceptible to disruptions. Various polymorphisms in the neurotransmitter genes are reported to increase the risk of developing dependence. The present study aimed to identify association of serotonin and GABA polymorphisms with AD in Indian subjects. Method The study group comprised of 141 AD cases recruited as per DSM IV TR criteria from the outpatient Department of Psychiatry and 110 volunteers from the general population. Clinical and family history was noted and 5 ml blood drawn for genetic studies. Polymorphisms 5-HTTLPR and STin2 of serotonin and rs2279020 and rs3219151 of the GABA pathway were analyzed and results correlated with age at first use quantity consumed, duration of use, dependence and age at onset of dependence. Results The marker frequencies were similar between cases and controls except for rs3219151. 5-HTTLPR was significantly associated with high AUDIT scores and alcohol intake (p Conclusions This preliminary study, though on a smaller sample size, suggests an association of 5-HTTLPR and GABAA receptor polymorphisms with AD in our population.

Biofertilizers are substances which contain living microorganisms which when applied to a soil promote the growth by increasing the supply or availability of primary nutrients to the host plant. Biofertilizers are usually prepared as a carrier based inoculants containing effective microorganism which would show a good relationship with the host plant. This makes it easy to handle with wide range of acceptance by the host. Rhizobia are a special type of bacteria which live in root nodules in symbiotic association and fix atmospheric free nitrogen and make it available to the plants. In this study Rhizobium is isolated and cultured from the root nodules of Pisum sativum (pea plant) in a selective media i.e. YEMA (Yeast Extract Mannitol Agar medium with Congo Red). The isolate was found with poor absorption of congo red and appeared as whitish gummy colony which was biochemically tested. The isolated strain was then mixed with carrier and applied on pea. Uninoculated soil was used as control. The growth of plants was observed at regular time intervals. The growth parameters observed were germination of seed, shoot initiation, root initiation, root length and shoot length. The seed started to germinate by day 2. After 20 days the plant with the biofertilizer showed a shoot length of 11.5cm and root length of 18cm while control showed 7cm and 9cm respectively. This report showed that application of isolated rhizobial strain enhanced the growth of plant. The isolated strain can be used as biofertilizer.

Phytoremediation, a growing sector of bioremediation, exploits the natural ability of a large variety of plants to filter chemicals through their root systems and to aerate the soil, allowing different microorganisms to grow. Phytoremediation has many advantages over other existing technologies in terms of safe and nondisturbing natural surroundings of contaminated sites. The modification in technology leads to different methods of phytoremediation, including phytotransformation, rhizoremediation, phytostabilization, phytoextraction and rhizofiltration. The application of a selected method depends on the nature and site of contaminant. To understand the mechanism of hyperaccumulation, various studies have been conducted on model (Arabidopsis thaliana) and commonly grown plants such as Populus, Brassica, Hydrilla etc. in phytoremediation. Further, based on mechanism and identified genes such as those involved in uptake, sequestration, remobilization and homeostasis, transgenic plants were designed and used efficiently to remove heavy metals and organic chemicals from the soil. However, further efforts are required for advancements in efficiency and robustness of transgenic plants and to popularize the phytoremediation technology on a commercial scale.

The present investigation is carried out to study the effect of leaf litter extract on the other crop. Allelopathic is the, phytotoxic effect of plants leaf on the other plants is well known. Some plants whether orchard crop or forest trees releases some chemicals which effects negatively sometimes positively to the growth of the other plants. In the present study it was studied that how the soil treated with leaf litter powder of trees (Litchi, Mango, Forest tree) is effected the growth and development of other plant. In an orchard generally leaf litter is the important source of allelochemicals in the soil. Litchi, Mango and forest litter all inhibit the growth of the test crop(Rice) but maximum inhibition is recorded by Litchi leaf powder treatment followed by mango and Forest whether Agriculture soil is treated as control in this case. Germination %, MDA content, Root shoot dry weight is highly affected but chlorophyll was maximum recorded from litchi leaf treatment.