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

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

Characterization and Reconstruction of Nanolipoprotein Particles (Nlps) by Cryo-EM and Image Reconstruction

Nanolipoprotein particles (NLPs) are small 10-20 nm diameter assemblies of apolipoproteins and lipids. At Lawrence Livermore National Laboratory (LLNL), they have constructed multiple variants of these assemblies. NLPs have been generated from a variety of lipoproteins, including apolipoprotein Al, apolipophorin III, apolipoprotein E4 22K, and MSP1T2 (nanodisc, Inc.). Lipids used included DMPC (bulk of the bilayer material), DMPE (in various amounts), and DPPC. NLPs were made in either the absence or presence of the detergent cholate. They have collected electron microscopy data as a part of the characterization component of this research. Although purified by size exclusion chromatography (SEC), samples are somewhat heterogeneous when analyzed at the nanoscale by negative stained cryo-EM. Images reveal a broad range of shape heterogeneity, suggesting variability in conformational flexibility, in fact, modeling studies point to dynamics of inter-helical loop regions within apolipoproteins as being a possible source for observed variation in NLP size. Initial attempts at three-dimensional reconstructions have proven to be challenging due to this size and shape disparity. They are pursuing a strategy of computational size exclusion to group particles into subpopulations based on average particle diameter. They show here results from their ongoing efforts at statistically and computationally subdividing NLP populations to realize greater homogeneity and then generate 3D reconstructions

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

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle.

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and United States of America), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs

On the need for an international effort to capture, share and use crystallization screening data

Development of an ontology for the description of crystallization experiments and results is proposed

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens

<div><p>Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle.</p></div