Interspecies Horizontal Transfer and Specific Integration of the Mosquitocidal Toxin-Encoding Plasmid pTAND672-2 from Bacillus thuringiensis subsp. to Lysinibacillus sphaericus.

pTAND672-2, a 144-kb resident plasmid of Bacillus thuringiensis serovar strain TAND672, was sequenced and characterized. This extrachromosomal element carries mosquitocidal toxin-, conjugation-, and recombinase-encoding genes, together with a putative arbitrium system, a genetic module recently discovered in temperate phages controlling lysogeny-lysis transition and in mobile genetic elements (MGEs) where its function remains clarified. Using conjugation experiments, pTAND672-2 is shown to be a novel integrative and conjugative element (ICE), which can horizontally transfer from B.

From bitter to delicious: properties and uses of microbial aminopeptidases.

Protein hydrolysates are easily digested and utilized by humans and animals, and are less likely to cause allergies. Protein hydrolysis caused by endopeptidases often leads to the exposure of hydrophobic amino acids at the ends of peptides, which consequently causes bitter taste. Microbial aminopeptidases remove the exposed hydrophobic amino acids at the ends of aminopeptides, which improves taste, allowing for easier production.

Characterization and heterologous expression of a novel Co-dependent leucyl aminopeptidase Amp0279 originating from Lysinibacillus sphaericus.

This study aims to explore the potential aminopeptidases of Lysinibacillus sphaericus based on the unique metabolic characteristics of this species which cannot metabolize carbohydrates and may have a strong ability to metabolize amino acids. Fifteen peptidase-encoding genes predicted in L. sphaericus C3-41 have been heterologously expressed in Escherichia coli BL21, and of these genes, only Amp0279 shows a high ability to hydrolyze L-leucine-4-nitroanilide (Leu-pNA).

Efficient Robust Estimation for Linear Models with Missing Response at Random.

Coefficient estimation in linear regression models with missing data is routinely done in the mean regression framework. However, the mean regression theory breaks down if the error variance is infinite. In addition, correct specification of the likelihood function for existing imputation approach is often challenging in practice, especially for skewed data.

Empirical Likelihood for Estimating Equations with Nonignorably Missing Data.

We develop an empirical likelihood (EL) inference on parameters in generalized estimating equations with nonignorably missing response data. We consider an exponential tilting model for the nonignorably missing mechanism, and propose modified estimating equations by imputing missing data through a kernel regression method. We establish some asymptotic properties of the EL estimators of the unknown parameters under different scenarios.