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The marine nitrogen cycle controls oceanic productivity through enzymatic processes mediated by microbes. Here, we report the construction, evaluation, and application of the OceansN CodeSet for the NanoString nCounter, which quantifies a suite of protein‐coding genes that are central to microbially mediated nitrogen cycle processes in the ocean. We also placed emphasis on quantifying a diverse set of marine diazotrophs within known nifH phylogenetic clades. The OceansN CodeSet provided direct hybridization‐based quantitation of 48 probes in a single sample, presenting advantages in terms of reduced sample handling, elimination of amplification bias, minimal DNA sample requirements, and the ability to assess targets ranging from relatively rare to abundant, with a reliable quantitation limit of ~ 1000 gene copies per target per sample. As such, our approach fills a unique methodological niche between the scale of high‐throughput amplicon sequencing (a compositional method) and quantitative polymerase chain reaction (qPCR) (a targeted method with generally lower throughput). When applied to North Atlantic environmental DNA samples, the OceansN CodeSet revealed temporal and spatial patterns in nitrogen assimilation, nitrification, and denitrification, as well as the abundance and distribution of various nitrogen‐fixing microorganisms (diazotrophs). Data from the nCounter was validated via internal and external controls, and by comparison to qPCR, nifH amplicon sequencing, and shotgun metagenomic sequencing. [ABSTRACT FROM AUTHOR]

Introduction: Congenital anomalies account for 8-15% of perinatal death and 13-16% of neonatal death in India[1]. A study of distribution of congenital anomalies and their early detection allows decisions to be made regarding termination of pregnancy, in-utero treatment, mode of delivery, postpartum management, counselling of the parents regarding prognosis and risk of recurrence. Methodology: A prospective enrolment of all consenting pregnant women delivering anomalous newborns within 1 year of study period was done. All study variables were studied in detail. Antenatal ultrasound of all women was noted for weeks of gestation, any fetal anomaly, any liquor or placental abnormality. At the time of delivery, all babies were analysed for gross congenital anomalies. Results: 33.33% anomalous babies were born to mothers of age group of 30-39 years. 50% women had significant past medical and/or family history. 26.66% of anomalous babies were associated with anaemia in pregnant women. 66.66% cases were detected by ultrasonography, while 26.6% cases were missed on USG. 76.66% anomalies were detected between 28 to 36 weeks of gestational age. Most commonly involved system is central nervous system in 53.33% cases followed by Musculoskeletal system in 40% cases. Conclusion: The study emphasizes on preventive measures for congenital anomaly such as, premarital counselling, periconceptional care in the form of improving maternal nutrition, folic acid supplementation, avoidance of teratogenic agents and the need of anomaly scan in second trimester for early diagnosis of congenital anomalies and their termination to prevent perinatal morbidity and mortality. [ABSTRACT FROM AUTHOR]

Problem statement: Rhizobial isolates belonging to genera (Rhizobium sp. and Mesorhizobium sp.) in our laboratory produced only catecholate type of siderophores. Although FhuA and FegA (ferrichrome receptors) homologs were found to be present in the sequenced genomes of few rhizobia (e.g., 1 in R. etli and 2 in Mesorhizobium sp. BNC1), laboratory isolates of the corresponding genera failed to utilize ferrichrome, a siderophore which is present in nanomolar concentrations in the soil. This inability was considered as a negative fitness factor with respect to rhizospheric colonization by these rhizobia. Approach: The 2.4 kb fegA gene (encoding ferrichrome receptor) was amplified along with its native promoter from Bradyrhizobium japonicum 61A152 and cloned in a broad host range plasmid vector pUCPM18. The plasmid construct pFJ was transferred by conjugation into Rhizobium sp. ST1 to give transconjugant ST1pFJ12. The consequence of FegA expression on the transconjugant was tested under lab and soil conditions, using physiological experiments. Results: Ability of the transconjugant ST1pFJ12 to utilize ferrichrome and expression of a 79 kD protein band on the outer membrane of the transconjugant confirmed FegA expression. Transconjugant ST1pFJ12 exhibited increased growth rate as compared to the parent strain ST1, in minimal media containing ferrichrome as the sole iron source, confirming the positive effect of FegA expression. Inoculation of pigeon pea seedlings with transconjugant ST1pFJ12 led to a marked increase in plant growth parameters as compared to plants inoculated with the parent strain ST1, the effect being more pronounced when Ustilago maydis, a ferrichrome producer was co-inoculated in the systems. Nodule occupancy on pigeon pea plant when inoculated with the transconjugant ST1pFJ12 alone was 57% which increased to 66% when co-inoculated with U. maydis as compared with 37 and 30% respectively, seen with parental strain ST1 inoculation. Conclusion: The clear increase in nodule occupancy and higher rhizospheric colonization by the fegA transconjugants, presented in this study together with the previous research reported from our laboratory, led us to conclude that ferrichrome utilization ability played an important role in the rhizospheric colonization of the bioinoculant strains. Testing the ability to utilize hydroxamate siderophores therefore, holds prime importance in selecting an efficient biofertilizer strain. Key words: Ferrichrome, rhizobia, rhizospheric colonization, cross-utilization, nodule occupancy, INTRODUCTION Although iron is the fourth most abundant element on the Earth, it is mainly present in its oxidized state, having a solubility of 10-18M at biological pH[1], which is [...]

Oligotrophic ocean gyre ecosystems may be expanding due to rising global temperatures [1–5]. Models predicting carbon flow through these changing ecosystems require accurate descriptions of phytoplankton communities and their metabolic activities [6]. We therefore measured distributions and activities of cyanobacteria and small photosynthetic eukaryotes throughout the euphotic zone on a zonal transect through the South Pacific Ocean, focusing on the ultraoligotrophic waters of the South Pacific Gyre (SPG). Bulk rates of CO2 fixation were low (0.1 µmol C l−1 d−1) but pervasive throughout both the surface mixed-layer (upper 150 m), as well as the deep chlorophyll a maximum of the core SPG. Chloroplast 16S rRNA metabarcoding, and single-cell 13CO2 uptake experiments demonstrated niche differentiation among the small eukaryotes and picocyanobacteria. Prochlorococcus abundances, activity, and growth were more closely associated with the rims of the gyre. Small, fast-growing, photosynthetic eukaryotes, likely related to the Pelagophyceae, characterized the deep chlorophyll a maximum. In contrast, a slower growing population of photosynthetic eukaryotes, likely comprised of Dictyochophyceae and Chrysophyceae, dominated the mixed layer that contributed 65–88% of the areal CO2 fixation within the core SPG. Small photosynthetic eukaryotes may thus play an underappreciated role in CO2 fixation in the surface mixed-layer waters of ultraoligotrophic ecosystems. [ABSTRACT FROM AUTHOR]

Abstract Background Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have been used in identifying remote homologues with considerable success. These conservation patterns arise from fold specific signals, shared across multiple families, and function specific signals unique to the families. The availability of sequences pre-classified according to their function permits the use of negative training sequences to improve the specificity of the HMM, both by optimizing the threshold cutoff and by modifying emission probabilities to minimize the influence of fold-specific signals. A protocol to generate family specific HMMs is described that first constructs a profile HMM from an alignment of the family's sequences and then uses this model to identify sequences belonging to other classes that score above the default threshold (false positives). Ten-fold cross validation is used to optimise the discrimination threshold score for the model. The advent of fast multiple alignment methods enables the use of the profile alignments to align the true and false positive sequences, and the resulting alignments are used to modify the emission probabilities in the original model. Results The protocol, called HMM-ModE, was validated on a set of sequences belonging to six sub-families of the AGC family of kinases. These sequences have an average sequence similarity of 63% among the group though each sub-group has a different substrate specificity. The optimisation of discrimination threshold, by using negative sequences scored against the model improves specificity in test cases from an average of 21% to 98%. Further discrimination by the HMM after modifying model probabilities using negative training sequences is provided in a few cases, the average specificity rising to 99%. Similar improvements were obtained with a sample of G-Protein coupled receptors sub-classified with respect to their substrate specificity, though the average sequence identity across the sub-families is just 20.6%. The protocol is applied in a high-throughput classification exercise on protein kinases. Conclusion The protocol has the potential to maximise the contributions of discriminating residues to classify proteins based on their molecular function, using pre-classified positive and negative sequence training data. The high specificity of the method, and increasing availability of pre-classified sequence data holds the potential for its application in sequence annotation.