A streamlined approach to structure elucidation using in cellulo crystallized recombinant proteins, InCellCryst.

With the advent of serial X-ray crystallography on microfocus beamlines at free-electron laser and synchrotron facilities, the demand for protein microcrystals has significantly risen in recent years. However, by in vitro crystallization extensive efforts are usually required to purify proteins and produce sufficiently homogeneous microcrystals. Here, we present InCellCryst, an advanced pipeline for producing homogeneous microcrystals directly within living insect cells. Our baculovirus-based cloning system enables the production of crystals from completely native proteins as well as the screening of different cellular compartments to maximize chances for protein crystallization. By optimizing cloning procedures, recombinant virus production, crystallization and crystal detection, X-ray diffraction data can be collected 24 days after the start of target gene cloning. Furthermore, improved strategies for serial synchrotron diffraction data collection directly from crystals within living cells abolish the need to purify the recombinant protein or the associated microcrystals.

Secretory IgA impacts the microbiota density in the human nose.

BACKGROUND: Respiratory mucosal host defense relies on the production of secretory IgA (sIgA) antibodies, but we currently lack a fundamental understanding of how sIgA is induced by contact with microbes and how such immune responses may vary between humans. Defense of the nasal mucosal barrier through sIgA is critical to protect from infection and to maintain homeostasis of the microbiome, which influences respiratory disorders and hosts opportunistic pathogens. METHODS: We applied IgA-seq analysis to nasal microbiota samples from male and female healthy volunteers, to identify which bacterial genera and species are targeted by sIgA on the level of the individual host. Furthermore, we used nasal sIgA from the same individuals in sIgA deposition experiments to validate the IgA-seq outcomes. CONCLUSIONS: We observed that the amount of sIgA secreted into the nasal mucosa by the host varied substantially and was negatively correlated with the bacterial density, suggesting that nasal sIgA limits the overall bacterial capacity to colonize. The interaction between mucosal sIgA antibodies and the nasal microbiota was highly individual with no obvious differences between potentially invasive and non-invasive bacterial species. Importantly, we could show that for the clinically relevant opportunistic pathogen and frequent nasal resident Staphylococcus aureus, sIgA reactivity was in part the result of epitope-independent interaction of sIgA with the antibody-binding protein SpA through binding of sIgA Fab regions. This study thereby offers a first comprehensive insight into the targeting of the nasal microbiota by sIgA antibodies. It thereby helps to better understand the shaping and homeostasis of the nasal microbiome by the host and may guide the development of effective mucosal vaccines against bacterial pathogens. Video Abstract.

Thought experiment: Decoding cognitive processes from the fMRI data of one individual.

Cognitive processes, such as the generation of language, can be mapped onto the brain using fMRI. These maps can in turn be used for decoding the respective processes from the brain activation patterns. Given individual variations in brain anatomy and organization, analyzes on the level of the single person are important to improve our understanding of how cognitive processes correspond to patterns of brain activity. They also allow to advance clinical applications of fMRI, because in the clinical setting making diagnoses for single cases is imperative. In the present study, we used mental imagery tasks to investigate language production, motor functions, visuo-spatial memory, face processing, and resting-state activity in a single person. Analysis methods were based on similarity metrics, including correlations between training and test data, as well as correlations with maps from the NeuroSynth meta-analysis. The goal was to make accurate predictions regarding the cognitive domain (e.g. language) and the specific content (e.g. animal names) of single 30-second blocks. Four teams used the dataset, each blinded regarding the true labels of the test data. Results showed that the similarity metrics allowed to reach the highest degrees of accuracy when predicting the cognitive domain of a block. Overall, 23 of the 25 test blocks could be correctly predicted by three of the four teams. Excluding the unspecific rest condition, up to 10 out of 20 blocks could be successfully decoded regarding their specific content. The study shows how the information contained in a single fMRI session and in each of its single blocks can allow to draw inferences about the cognitive processes an individual engaged in. Simple methods like correlations between blocks of fMRI data can serve as highly reliable approaches for cognitive decoding. We discuss the implications of our results in the context of clinical fMRI applications, with a focus on how decoding can support functional localization.