A fixed-target platform for serial femtosecond crystallography in a hydrated environment.

For serial femtosecond crystallography at X-ray free-electron lasers, which entails collection of single-pulse diffraction patterns from a constantly refreshed supply of microcrystalline sample, delivery of the sample into the X-ray beam path while maintaining low background remains a technical challenge for some experiments, especially where this methodology is applied to relatively low-ordered samples or those difficult to purify and crystallize in large quantities. This work demonstrates a scheme to encapsulate biological samples using polymer thin films and graphene to maintain sample hydration in vacuum conditions. The encapsulated sample is delivered into the X-ray beam on fixed targets for rapid scanning using the Roadrunner fixed-target system towards a long-term goal of low-background measurements on weakly diffracting samples. As a proof of principle, we used microcrystals of the 24 kDa rapid encystment protein (REP24) to provide a benchmark for polymer/graphene sandwich performance. The REP24 microcrystal unit cell obtained from our sandwiched in-vacuum sample was consistent with previously established unit-cell parameters and with those measured by us without encapsulation in humidified helium, indicating that the platform is robust against evaporative losses. While significant scattering from water was observed because of the sample-deposition method, the polymer/graphene sandwich itself was shown to contribute minimally to background scattering

Regulation of Yersina pestis Virulence by AI-2 Mediated Quorum Sensing

The proposed research was motivated by an interest in understanding Y. pestis virulence mechanisms and bacteria cell-cell communication. It is expected that a greater understanding of virulence mechanisms will ultimately lead to biothreat countermeasures and novel therapeutics. Y. pestis is the etiological agent of plague, the most devastating disease in human history. Y. pestis infection has a high mortality rate and a short incubation before mortality. There is no widely available and effective vaccine for Y. pestis and multi-drug resistant strains are emerging. Y. pestis is a recognized biothreat agent based on the wide distribution of the bacteria in research laboratories around the world and on the knowledge that methods exist to produce and aerosolize large amounts of bacteria. We hypothesized that cell-cell communication via signaling molecules, or quorum sensing, by Y. pestis is important for the regulation of virulence factor gene expression during host invasion, though a causative link had never been established. Quorum sensing is a mode of intercellular communication which enables orchestration of gene expression for many bacteria as a function of population density and available evidence suggests there may be a link between quorum sensing and regulation of Y. pesits virulence. Several pathogenic bacteria have been shown to regulate expression of virulence factor genes, including genes encoding type III secretion, via quorum sensing. The Y. pestis genome encodes several cell-cell signaling pathways and the interaction of at least three of these are thought to be involved in one or more modes of host invasion. Furthermore, Y. pestis gene expression array studies carried out at LLNL have established a correlation between expression of known virulence factors and genes involved in processing of the AI-2 quorum sensing signal. This was a basic research project that was intended to provide new insights into bacterial intercellular communication and how it is used to regulate virulence in Y. pestis. It is known that many bacteria use intercellular signaling molecules to orchestrate gene expression and cellular function. A fair amount is known about production and uptake of signaling molecules, but very little is known about how intercellular signaling regulates other pathways. Although several studies demonstrate that intercellular signaling plays a role in regulating virulence in other pathogens, the link between signaling and regulation of virulence has not been established. Very little work had been done directly with Y. pestis intercellular signaling apart from the work carried out at LLNL. The research we proposed was intended to both establish a causative link between AI-2 intercellular signaling and regulation of virulence in Y. pestis and elucidate the fate of the AI-2 signaling molecule after it is taken up and processed by Y. pestis. Elucidating the fate of AI-2 was expected to lead directly to the understanding of how AI-2 signal processing regulates other pathways as well as provide new insights in this direction

Characterization and Purification of Polydisperse Reconstituted Lipoproteins and Nanolipoprotein Particles

Heterogeneity is a fact that plagues the characterization and application of many self-assembled biological constructs. The importance of obtaining particle homogeneity in biological assemblies is a critical goal, as bulk analysis tools often require identical species for reliable interpretation of the results—indeed, important tools of analysis such as x-ray diffraction typically require over 90% purity for effectiveness. This issue bears particular importance in the case of lipoproteins. Lipid-binding proteins known as apolipoproteins can self assemble with liposomes to form reconstituted high density lipoproteins (rHDLs) or nanolipoprotein particles (NLPs) when used for biotechnology applications such as the solubilization of membrane proteins. Typically, the apolipoprotein and phospholipids reactants are self assembled and even with careful assembly protocols the product often contains heterogeneous particles. In fact, size polydispersity in rHDLs and NLPs published in the literature are frequently observed, which may confound the accurate use of analytical methods. In this article, we demonstrate a procedure for producing a pure, monodisperse NLP subpopulation from a polydisperse self-assembly using size exclusion chromatography (SEC) coupled with high resolution particle imaging by atomic force microscopy (AFM). In addition, NLPs have been shown to self assemble both in the presence and absence of detergents such as cholate, yet the effects of cholate on NLP polydispersity and separation has not been systematically examined. Therefore, we examined the separation properties of NLPs assembled in both the absence and presence of cholate using SEC and native gel electrophoresis. From this analysis, NLPs prepared with and without cholate showed particles with well defined diameters spanning a similar size range. However, cholate was shown to have a dramatic affect on NLP separation by SEC and native gel electrophoresis. Furthermore, under conditions where different sized NLPs were not sufficiently separated or purified by SEC, AFM was used to deconvolute the elution pattern of different sized NLPs. From this analysis we were able to purify an NLP subpopulation to 90% size homogeneity by taking extremely fine elutions from the SEC. With this purity, we generate high quality NLP crystals that were over 100 μm in size with little precipitate, which could not be obtained utilizing the traditional size exclusion techniques. This purification procedure and the methods for validation are broadly applicable to other lipoprotein particles

Atomic force microscopy differentiates discrete size distributions between membrane protein containing and empty nanolipoprotein particles

AbstractTo better understand the incorporation of membrane proteins into discoidal nanolipoprotein particles (NLPs) we have used atomic force microscopy (AFM) to image and analyze NLPs assembled in the presence of bacteriorhodopsin (bR), lipoprotein E4 n-terminal 22k fragment scaffold and DMPC lipid. The self-assembly process produced two distinct NLP populations: those containing inserted bR (bR-NLPs) and those that did not (empty-NLPs). The bR-NLPs were distinguishable from empty-NLPs by an average increase in height of 1.0 nm as measured by AFM. Streptavidin binding to biotinylated bR confirmed that the original 1.0 nm height increase corresponds to br-NLP incorporation. AFM and ion mobility spectrometry (IMS) measurements suggest that NLP size did not vary around a single mean but instead there were several subpopulations, which were separated by discrete diameters. Interestingly, when bR was present during assembly the diameter distribution was shifted to larger particles and the larger particles had a greater likelihood of containing bR than smaller particles, suggesting that membrane proteins alter the mechanism of NLP assembly

Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds

Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. Methods Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. Results In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. Conclusions Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available

Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Farmed Atlantic Salmon

Genomic selection uses genome-wide marker information to predict breeding values for traits of economic interest, and is more accurate than pedigree-based methods. The development of high density SNP arrays for Atlantic salmon has enabled genomic selection in selective breeding programmes, alongside high-resolution association mapping of the genetic basis of complex traits. However, in sibling testing schemes typical of salmon breeding programmes, trait records are available on many thousands of fish with close relationships to the selection candidates. Therefore, routine high density SNP genotyping may be prohibitively expensive. One means to reducing genotyping cost is the use of genotype imputation, where selected key animals (e.g. breeding programme parents) are genotyped at high density, and the majority of individuals (e.g. performance tested fish and selection candidates) are genotyped at much lower density, followed by imputation to high density. The main objectives of the current study were to assess the feasibility and accuracy of genotype imputation in the context of a salmon breeding programme. The specific aims were: (i) to measure the accuracy of genotype imputation using medium (25 K) and high (78 K) density mapped SNP panels, by masking varying proportions of the genotypes and assessing the correlation between the imputed genotypes and the true genotypes; and (ii) to assess the efficacy of imputed genotype data in genomic prediction of key performance traits (sea lice resistance and body weight). Imputation accuracies of up to 0.90 were observed using the simple two-generation pedigree dataset, and moderately high accuracy (0.83) was possible even with very low density SNP data (~250 SNPs). The performance of genomic prediction using imputed genotype data was comparable to using true genotype data, and both were superior to pedigree-based prediction. These results demonstrate that the genotype imputation approach used in this study can provide a cost-effective method for generating robust genome-wide SNP data for genomic prediction in Atlantic salmon. Genotype imputation approaches are likely to form a critical component of cost-efficient genomic selection programmes to improve economically important traits in aquaculture

Genetic selection for bovine chromosome 18 haplotypes associated with divergent somatic cell score affects postpartum reproductive and metabolic performance

The susceptibility of animals to periparturient diseases has a great effect on the economic efficiency of dairy industries, on the frequency of antibiotic treatment, and on animal welfare. The use of selection for breeding cows with reduced susceptibility to diseases offers a sustainable tool to improve dairy cattle farming. Several studies have focused on the association of distinct bovine chromosome 18 genotypes or haplotypes with performance traits. The aim of this study was to test whether selection of Holstein Friesian heifers via SNP genotyping for alternative paternal chromosome 18 haplotypes associated with favorable (Q) or unfavorable (q) somatic cell scores influences postpartum reproductive and metabolic diseases. Thirty-six heifers (18 Q and 18 q) were monitored from 3 wk before calving until necropsy on d 39 (± 4 d) after calving. Health status and rectal temperature were measured daily, and body condition score and body weight were assessed once per week. Blood samples were drawn twice weekly, and levels of insulin, nonesterified fatty acids, insulin-like growth factor-I, growth hormone, and β-hydroxybutyrate were measured. Comparisons between the groups were performed using Fisher's exact test, chi-squared test, and the GLIMMIX procedure in SAS. Results showed that Q-heifers had reduced incidence of metritis compared with q-heifers and were less likely to develop fever. Serum concentrations of β-hydroxybutyrate were lower and insulin-like growth factor-I plasma concentrations were higher in Q- compared with q-heifers. However, the body condition score and withers height were comparable between haplotypes, but weight loss tended to be lower in Q-heifers compared with q-heifers. No differences between the groups were detected concerning retained fetal membranes, uterine involution, or onset of cyclicity. In conclusion, selection of chromosome 18 haplotypes associated with a reduced somatic cell score resulted in a decreased incidence of postpartum reproductive and metabolic diseases in this study. The presented data add to the existing knowledge aimed at avoiding negative consequences of genetic selection strategies in dairy cattle farming. The underlying causal mechanisms modulated by haplotypes in the targeted genomic region and immune competence necessitate further investigation