Sama Kalyana Chakravarthy- PostDoc Position at L V Prasad Eye Institute
Sama Kalyana Chakravarthy
- PostDoc Position at L V Prasad Eye Institute
About
44
Publications
12,300
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861
Citations
Introduction
Current institution
Additional affiliations
June 2005 - January 2011
Position
- PhD Student
Description
- Anoxygenic phototrophic bacterial diversity from marine habitats
Publications
Publications (44)
Inflammation of the cornea is known as keratitis, and bacteria, fungi, protozoans, and viruses are the etiological agents of this disease. Delayed treatment of keratitis could result in loss of vision and, under certain severity conditions, the removal of an eye and its associated structures. In the current study, the ocular surface (conjunctiva an...
Studies have documented dysbiosis in the gut mycobiome in people with Type 2 diabetes mellitus (T2DM). However, it is not known whether dysbiosis in the gut mycobiome of T2DM patients would be reflected in people with diabetic retinopathy (DR) and if so, is the observed mycobiome dysbiosis similar in people with T2DM and DR. Gut mycobiomes were gen...
Microbial keratitis is an infectious disease of the eye, in which the cornea is inflamed. Under severe conditions, keratitis can lead to significant loss of vision and enucleation of the eye. Ocular trauma is the major risk factor causing keratitis and microorganisms viz., bacteria, fungi, viruses are the causative agents. The current study charact...
Fungi have been associated with various diseases of the eye like keratitis, uveitis and endophthalmitis. Despite this fact, fungal microbiome (mycobiome) studies compared to the bacterial microbiome studies have remained neglected. In the present study, using metagenomic sequencing, the mycobiomes of the vitreous of healthy control individuals (VC,...
Keratitis, an inflammatory disease of the eye, when neglected could lead to sight-threatening complications and ultimately blindness. Globally, over a million people are affected by keratitis annually. Keratitis has a microbial etiology and is caused by bacteria, fungi, viruses, etc. The present study compared the ocular surface fungal microbiome o...
Purpose:
In this study, the gut fungal microbiome of uveitis (UVT) patients was generated and compared with healthy controls (HC) to identify dysbiosis in UVT patients and ascertain the role of gut fungal microbiome in disease pathology.
Methods:
In the present study, gut fungal microbiomes were analyzed in the fecal samples of HC (n = 24) and U...
Purpose:
To enumerate the ocular surface fungal microbiome of healthy human eyes by using next-generation sequencing (NGS).
Methods:
Tarsal and fornix conjunctiva from the lower and upper lids of both eyes of healthy individuals were swabbed in duplicate separately. A total of 34 samples were collected from both the eyes of 17 individuals, which...
[This corrects the article DOI: 10.1371/journal.pone.0199640.].
Dysbiosis, or imbalance in the gut microbiome, has been implicated in auto-immune, inflammatory, neurological diseases as well as in cancers. More recently it has also been shown to be associated with ocular diseases. In the present study, the association of gut microbiome dysbiosis with bacterial Keratitis, an inflammatory eye disease which signif...
Dysbiosis in the gut microbiome has been implicated in several diseases including auto-immune diseases, inflammatory diseases, cancers and mental disorders. Keratitis is an inflammatory disease of the eye significantly contributing to corneal blindness in the developing world. It would be worthwhile to investigate the possibility of dysbiosis in th...
Core OTUs of the fungal microbiome libraries (OTUs having ≥ 0.001% abundance in a sample and ubiquitously present in over 80% of the samples).
(DOC)
Relative abundances of bacterial phyla in the studied cohort.
Only those phyla having mean abundance > 1% are included in the table.
(XLSX)
Discriminating OTUs identified through pairwise Wilcoxon test between three groups of samples (Healthy Controls (HC) vs. Fungal Keratitis_Treated (FK_T), HC vs. Fungal Keratitis_UnTreated (FK_UT) and FK_T vs. FK_UT).
(DOC)
Relative abundances of KEGG pathways inferred from respective 16S taxonomic profiles of the studied cohort.
(XLSX)
Rarefaction curves of the fungal microbiome libraries of the 62 fecal samples from healthy controls and fungal Keratitis patients.
(TIF)
Details of healthy controls and fungal Keratitis patients.
(DOC)
Relative abundances of fungal OTUs for 62 fungal microbiomes.
Sparse OTUs (with < 0.001% reads) were removed.
(XLSX)
Details of sequencing reads for 62 fungal microbiomes.
(XLSX)
Results of Wilcoxon test to identify discriminating fungal taxa.
[results depicted at genera level; genera having median abundance > 0% in at least one class of samples (either FK or HC) included in table].
(DOC)
Relative abundances of bacterial OTUs for 58 bacterial microbiome libraries.
Sparse OTUs (with < 0.001% reads) were removed.
(XLSX)
Details of sequencing reads for 63 bacterial microbiomes.
(XLSX)
Relative abundances of bacterial families in the studied cohort.
Only those families having mean abundance > 1% are included in the table.
(XLSX)
Core OTUs in the bacterial microbiome libraries of both HC and FK samples.
(OTUs having ≥ 0.01% abundance in a sample and ubiquitously present in over 80% of the FK and HC samples).
(DOC)
Core OTUs (having ≥ 0.01% abundance in a sample and ubiquitously present in over 80% of the HC fecal samples) in the bacterial microbiome libraries of HC samples.
(DOCX)
Summary of KEGG pathways observed in the studied cohort.
The pathways that showed significantly different enrichment in each dataset were identified using Wilcoxon test (BH corrected P-value < 0.05 was considered as significant).
(XLSX)
Taxonomic abundances of different bacterial families, across HC and FK samples.
Only those families with > 1% mean abundance are depicted in the plot.
(TIF)
Relative abundances of fungal phyla in the studied cohort.
(XLSX)
Core OTUs (having ≥ 0.01% abundance in a sample and ubiquitously present in over 80% of the FK fecal samples) in the bacterial microbiome libraries of FK samples.
(DOC)
Relative abundances of KEGG modules inferred from respective 16S taxonomic profiles of the studied cohort.
(XLSX)
Summary of KEGG functional modules observed in the studied cohort.
The modules that showed significantly different enrichment in each dataset were identified using Wilcoxon test (BH corrected P-value < 0.05 was considered as significant).
(XLSX)
Rarefaction curves of the bacterial microbiome libraries of the 58 fecal samples from healthy controls and fungal Keratitis patients.
(TIF)
Uveitis (UVT), an inflammatory disease of the eye significantly contributes to vision impairment and blindness. Uveitis is associated with systemic infectious and autoimmune diseases, but in most cases, the aetiology remains unidentified. Dysbiosis in the gut microbiome has been implicated in autoimmune diseases, inflammatory diseases, cancers and...
Purpose:
To study antibiotic susceptibility and biofilm-forming potential of ocular isolates of Candida albicans along with gene expression.
Methods:
Seven clinical isolates of C. albicans (keratitis-6 and orbital cellulitis-1) were evaluated. Biofilm formation in one isolate was monitored by scanning electron microscopy (SEM) and confocal laser...
Two strains (JA266T and JA333) of Gram-negative, rod shaped, phototrophic, purple nonsulfur bacteria were isolated from a freshwater fish pond and an industrial effluent. Both phototrophic and chemotrophic growth is possible by both strains. Bacteriochlorophyll a and carotenoids of the spirilloxanthin series were present as photosynthetic pigments....
Fossil energy resources, the primary source of transport fuel in the world is depleting dramatically to meet the ever-increasing energy demands globally. Crop plants are one of the best sources of renewable energy which can be used as feedstock for biofuel production. Sweet sorghum [Sorghum bicolor (L.) Moench], a C4 Graminaceous crop which has sug...
Four strains (JA310(T), JA531(T), JA447 and JA490) of red to reddish brown pigmented, rod-shaped, motile and budding phototrophic bacteria were isolated from soil and freshwater sediment samples from different geographical regions of India. All strains contained bacteriochlorophyll a and carotenoids of the spirilloxanthin series. The major cellular...
Two strains (JA492(T) and JA590) of spiral-shaped, anaerobic, Gram-stain-negative, motile, purple non-sulfur bacteria were isolated from aquatic sediments from a bird sanctuary and a stream, respectively, and were characterized by a polyphasic taxonomic approach. Bacteriochlorophyll a and carotenoids (rhodopin, lycopene, hydroxylycopene glucoside a...
An ovoid-rod-shaped, phototrophic, purple non-sulfur bacterium, designated strain JA322(T), was isolated in pure culture from a water sample collected from a saline pond with purple-coloured water, located near Satpada in Orissa, India. Strain JA322(T) was Gram-negative and non-motile and grew photoheterotrophically with a number of organic compoun...
Two Gram-negative, vibrioid, phototrophic, purple non-sulfur strains, JA131T and JA135T, were isolated from marine habitats. Strain JA131T is non-motile but strain JA135T is motile by means of a pair of monopolar flagella. Both strains have an obligate requirement for NaCl for growth. The intracellular photosynthetic membranes of the two novel stra...
Questions
Question (1)
Hi, we are working on stool-metagenomics based on V3V4 and ITS2 amplicon sequencing. We would like to analyse data in a work station by using QIIME. Can someone help me with the best configuration (type of processor, RAM, hard disk storage) of work station that is required for analysing this NGS data (preferably for the data that is generated on an Illumina-MISeq platform; assuming for each sample nearly 2 GB of data is generated; and we need to analyse a maximum of about 120 such samples at a time).
