ENV-653: PRODUCTION OF BIOSURFACTANT BY RHODOCOCCUS ERYTHROPOLIS SP. CULTIVATED IN A NOVEL FISH WASTE COMPOST EXTRACT SUBSTRATE

Compost generated through fish waste composting could provide an effective source of nutrient-rich organic matter for microbial growth, leading to the production of valuable products such as biosurfactants. Existing biosurfactant production is a relative expensive process and raw materials contribute about 30% of the production cost. Utilizing waste streams such as fish waste compost (FWC) as a substrate is an economically viable alternative. In this study, biosurfactant was produced by Rhodococcus erythropolis sp. P6-4P, a strain isolated from the North Atlantic Ocean. Biosurfactant production with FWC extract was compared with other soluble and insoluble carbon and nitrogen sources using emulsification assay and surface tension measurement. FWC extract showed good potential as an unconventional source of nutrient for microbial growth. The produced biosurfactant under optimum condition obtained via response surface methodology was further characterized for total carbohydrate, total lipid and total protein content. The results provided evidence for using FWC extract as a novel substrate for biosurfactant production

Cerebellar-dependent delay eyeblink conditioning in adolescents with Specific Language Impairment

Cerebellar impairments have been hypothesized as part of the pathogenesis of Specific Language Impairment (SLI), although direct evidence of cerebellar involvement is sparse. Eyeblink Conditioning (EBC) is a learning task with well documented cerebellar pathways. This is the first study of EBC in affected adolescents and controls. 16 adolescent controls, 15 adolescents with SLI, and 12 adult controls participated in a delay EBC task. Affected children had low general language performance, grammatical deficits but no speech impairments. The affected group did not differ from the control adolescent or control adult group, showing intact cerebellar functioning on the EBC task. This study did not support cerebellar impairment at the level of basic learning pathways as part of the pathogenesis of SLI. Outcomes do not rule out cerebellar influences on speech impairment, or possible other forms of cerebellar functioning as contributing to SLI

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Modeling the Sorption of Ni2+ and Co2+ on Saprist Peat Using the Response Surface Methodology

A detailed study of the sorption of Ni2+ and Co2+ from simulated wastewater on saprist peat is presented. The significantly decomposed peat possessed a strong sorptive capacity that was maintained over a wide range of pH. With a metal concentration range of 50 to 200 mg/L, pH range of 3 to 10, peat dose of 2 to 40 g/L, and contact time of 12 to 24 h, batch experiments were conducted based on a four-factor Box-Behnken response surface design. The percentage removals of Ni2+ and Co2+ were analyzed using analysis of variance. Second order response surface models were developed with the significant factors and their interactions to predict the percentage sorption of Ni2+ and Co2+ independently. The prediction equations were verified with additional data not used in developing the equations. The study showed that the saprist peat could be a potential industrial metal adsorbent and the percentage of uptake of Ni2+ and Co2+ could be accurately predicted using the second order response surface models developed. Ni2+ uptake was greater for the two metals and reached a maximum value at just below a neutral pH and Co2+ uptake continued to increase from pH > 5, with higher uptake percentage at pH 10

Corrigendum to ‘Neurology of COVID-19 in Singapore (vol 418, 117118, 2020)

10.1016/j.jns.2021.117406JOURNAL OF THE NEUROLOGICAL SCIENCES42

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease