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Through machine learning, identifying correlations between amino acid sequences of antibodies and their observed characteristics, we developed an internal viscosity prediction model to empower the rapid engineering of therapeutic antibody candidates. For a highly viscous anti-IL-13 monoclonal antibody, we used a structure-based rational design strategy to generate a list of variants that were hypothesized to mitigate viscosity. Our viscosity prediction tool was then used as a screen to cull virtually engineered variants with a probability of high viscosity while advancing those with a probability of low viscosity to production and testing. By combining the rational design engineering strategy with the in silico viscosity prediction screening step, we were able to efficiently improve the highly viscous anti-IL-13 candidate, successfully decreasing the viscosity at 150 mg/mL from 34 cP to 13 cP in a panel of 16 variants.

Plants alter their gene expression patterns in response to drought. Sometimes these transcriptional changes are successful adaptations leading to tolerance, while in other instances the plant ultimately fails to adapt to the stress and is labeled as sensitive to that condition. We measured the expression of approximately half of the genes in rice ( approximately 21,000) in phenotypically divergent accessions and their transgressive segregants to associate stress-regulated gene expression changes with quantitative trait loci (QTLs) for osmotic adjustment (OA, a trait associated with drought tolerance). Among the parental lines, a total of 662 transcripts were differentially expressed. Only 12 genes were induced in the low OA parent, CT9993, at moderate dehydration stress levels while over 200 genes were induced in the high OA parent, IR62266. The high and low OA parents had almost entirely different transcriptional responses to dehydration stress suggesting a complete absence of an appropriate response rather than a slower response in CT9993. Sixty-nine genes were up-regulated in all the high OA lines and nine of those genes were not induced in any of the low OA lines. The annotation of four of those genes, sucrose synthase, a pore protein, a heat shock and an LEA protein, suggests a role in maintaining high OA and membrane stability. Of the 3,954-probe sets that correspond to the QTL intervals, very few had a differential expression pattern between the high OA and low OA lines that suggest a role leading to the phenotypic variation. However, several promising candidates were identified for each of the five QTL including a snRNP auxiliary factor, a LEA protein, a protein phosphatase 2C and a Sar1 homolog.