Mapping Local Conformational Landscapes of Proteins in Solution

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In vivo monitoring blood‐brain barrier permeability using spectral imaging through optical clearing skull window

The blood‐brain barrier (BBB) plays a key role in the health of the central nervous system. Opening the BBB is very important for drug delivery to brain tissues to enhance the therapeutic effect on brain diseases. It is necessary to in vivo monitor the BBB permeability for assessing drug release with high resolution; however, an effective method is lacking. In this work, we developed a new method that combined spectral imaging with an optical clearing skull window to in vivo dynamically monitor BBB opening caused by 5‐aminolevulinic acid (5‐ALA)‐mediated photodynamic therapy (PDT), in which the Evans blue dye (EBd) acted as an indicator of the BBB permeability. Using this method, we effectively monitored the cerebrovascular EBd leakage process. Moreover, the analysis of changes in the vascular and extravascular EBd concentrations demonstrated that the PDT‐induced BBB opening exhibited spatiotemporal differences in the cortex. This spectral imaging method based on the optical clearing skull window provides a low‐cost and simply operated tool for in vivo monitoring BBB opening process. This has a high potential for the visualization of drug delivery to the central nervous system. Thus, it is of tremendous significance in brain disease therapy. Monitoring the changes in PDT‐induced BBB permeability by evaluating the EBd concentration using an optical clearing skull window. (A) Entire brains and coronal sections following treatment of PDT with/without an optical clearing skull window after injection of EBd. (B) Typical EBd distribution maps before and after laser irradiation captured by the spectral imaging method. (Colorbar represents the EBd concentration).      

Spectral histopathology of the lung: A review of two large studies

This paper summarizes results from two large lung cancer studies comprising over 700 samples that demonstrate the ability of spectral histopathology (SHP) to distinguish cancerous tissue regions from normal tissue, to differentiate benign lesions from normal tissue and cancerous lesions, and to classify lung cancer types. Furthermore, malignancy‐associated changes can be identified in cancer‐adjacent normal tissue. The ability to differentiate a multitude of normal cells and tissue types allow SHP to identify tumor margins and immune cell infiltration. Finally, SHP easily distinguishes small cell lung cancer (SCLC) from non‐SCLC (NSCLC) and provides a further differentiation of NSCLC into adenocarcinomas and squamous cell carcinomas with an accuracy comparable of classical histopathology combined with immunohistochemistry. Case studies are presented that demonstrates that SHP can resolve interobserver discrepancies in standard histopathology.     

Feed intake and performance of growing lambs raised on concentrate-based diets under cafeteria feeding systems

Two trials were undertaken to study the effects of cafeteria feeding systems on the feed intake, animal performance and carcass characteristics of growing lambs. Trial 1 was designed to compare conventional and cafeteria feeding systems in terms of the growth of individually reared lambs. For this assay, 26 weaned Merino lambs (15.5 ± 0.20 kg live weight) were assigned to three dietary treatment groups: (1) a control group fed barley straw and commercial concentrate under a conventional feeding system, (2) group W100S, fed soya-bean meal, whole barley grain and a mineral-vitamin supplement under a cafeteria feeding system, and (3) group W100S-T, fed as in the W100S treatment but allowing the lambs an initial training period so they could learn to identify a number of feeds. The feeding system had no significant effect ( P>0.05) on either average daily live-weight gain, carcass weight, or carcass conformation. The food conversion ratio was lower ( P < 0.05) for the cafeteria-reared animals (2.9 ± 0.16 v. 2.5 ± 0.08 g dry-matter intake per g average daily gain) than those of the control group. This might be related to the higher crude protein intake seen in the cafeteria groups (150 ± 5.6 v. 208 ± 12.5 g per animal per day; P < 0.001).In trial 2, cafeteria and conventional feeding system were compared in terms of the growth of feedlot lambs. Two hundred weaned Merino lambs (13.1 ± 0.10 kg) were divided into two experimental groups: (1) a control group, offered commercial concentrate and barley straw, and (2) a cafeteria group fed the same diet as W100ST in trial 1. The average daily gain (282 ± 5.8 and 309 ± 6.5; P < 0.01) was greater in the cafeteria than in the control group. Whereas neither carcass conformation nor fatness were affected by the feeding system, the dressing percentage was slightly higher ( P>0.001) in the conventional than in the cafeteria system lambs.The use of cafeteria systems for fattening lambs can improve the feed conversion efficiency and body growth rate over those achieved with conventional feeding systems, although the crude protein intake in these systems seems to be in excess of requirements.     

Automated work-flow for processing high-resolution direct infusion electrospray ionization mass spectral fingerprints

The use of mass spectrometry (MS) is pivotal in analyses of the metabolome and presents a major challenge for subsequent data processing. While the last few years have given new high performance instruments, there has not been a comparable development in data processing. In this paper we discuss an automated data processing pipeline to compare large numbers of fingerprint spectra from direct infusion experiments analyzed by high resolution MS. We describe some of the intriguing problems that have to be addressed, starting with the conversion and pre-processing of the raw data to the final data analysis. Illustrated on the direct infusion analysis (ESI-TOF-MS) of complex mixtures the method exploits the full quality of the high-resolution present in the mass spectra. Although the method is illustrated as a new library search method for high resolution MS, we demonstrate that the output of the preprocessing is applicable to cluster-, discriminant analysis, and related multivariate methods applied directly to mass spectra from direct infusion analysis of crude extracts. This is done to find the relationship between several terverticillate Penicillium species and identify the ions responsible for the segregation.     

A prostate cancer tissue specific spectral library for targeted proteomic analysis

Prostate cancer is the most common cancer in males worldwide. Mass spectrometry-based targeted proteomics has demonstrated great potential in quantifying proteins from formalin-fixed paraffin-embedded (FFPE) and (fresh) frozen biopsy tissues. Here we provide a comprehensive tissue-specific spectral library for targeted proteomic analysis of prostate tissue samples. Benign and malignant FFPE prostate tissue samples were processed into peptide samples by pressure cycling technology (PCT)-assisted sample preparation, and fractionated with high-pH reversed phase liquid chromatography (RPLC). Based on data-dependent acquisition (DDA) MS analysis using a TripleTOF 6600, we built a library containing 108,533 precursors, 84,198 peptides and 9384 unique proteins (1% FDR). The applicability of the library was demonstrated in prostate specimens.     

Expanding the Coverage of Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches

Genome-scale metabolomics analysis is increasingly used for pathway and function discovery in the post-genomics era. The great potential offered by developed mass spectrometry (MS)-based technologies has been hindered, since only a small portion of detected metabolites were identifiable so far. To address the critical issue of low identification coverage in metabolomics, we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases. The experimental reference spectra and in silico reference spectra were adopted to facilitate the structural annotation. To further characterize the structure of metabolites, two approaches were incorporated into our strategy, i.e., structural motif search combined with neutral loss scanning and metabolite association network. Untargeted metabolomics analysis was performed on 150 rice cultivars using ultra-performance liquid chromatography coupled with quadrupole-Orbitrap MS. Consequently, a total of 1939 out of 4491 metabolite features in the MS/MS spectral tag (MS2T) library were annotated, representing an extension of annotation coverage by an order of magnitude in rice. The differential accumulation patterns of flavonoids between indica and japonica cultivars were revealed, especially O-sulfated flavonoids. A series of closely-related flavonolignans were characterized, adding further evidence for the crucial role of tricin-oligolignols in lignification. Our study provides an important protocol for exploring phytochemical diversity in other plant species.     

Light capture and pigment diversity in marine and freshwater cryptophytes

Phenotypic traits associated with light capture and phylogenetic relationships were characterized in 34 strains of diversely pigmented marine and freshwater cryptophytes. Nuclear SSU and partial LSU rDNA sequence data from 33 of these strains plus an additional 66 strains produced a concatenated rooted maximum likelihood tree that classified the strains into 7 distinct clades. Molecular and phenotypic data together support: (i) the reclassification of Cryptomonas irregularis NIES 698 to the genus Rhodomonas, (ii) revision of phycobiliprotein (PBP) diversity within the genus Hemiselmis to include cryptophyte phycocyanin (Cr‐PC) 569, (iii) the inclusion of previously unidentified strain CCMP 2293 into the genus Falcomonas, even though it contains cryptophyte phycoerythrin 545 (Cr‐PE 545), and (iv) the inclusion of previously unidentified strain CCMP 3175, which contains Cr‐PE 545, in a clade with PC‐containing Chroomonas species. A discriminant analysis‐based model of group membership correctly predicted 70.6% of the clades using three traits: PBP concentration · cell^?1, the wavelength of PBP maximal absorption, and habitat. Non‐PBP pigments (alloxanthin, chl‐a, chl‐c₂, α‐carotene) did not contribute significantly to group classification, indicating the potential plasticity of these pigments and the evolutionary conservation of the PBPs. Pigment data showed evidence of trade‐offs in investments in PBPs vs. chlorophylls (a +c₂).     

Testing and interpreting the shared space‐environment fraction in variation partitioning analyses of ecological data

Variation partitioning analyses combined with spatial predictors (Moran's eigenvector maps, MEM) are commonly used in ecology to test the fractions of species abundance variation purely explained by environment and space. However, while these pure fractions can be tested using a classical residuals permutation procedure, no specific method has been developed to test the shared space‐environment fraction (SSEF). Yet, the SSEF is expected to encompass a major driver of community assembly, that is, an induced spatial dependence effect (ISD; i.e. the reflection of a spatially structured habitat filter on a species distribution). A reliable test of this fraction is therefore crucial to properly test the presence of an ISD on ecological data. To bridge the gap, we propose to test the SSEF through spatially‐constrained null models: torus‐translations, and Moran spectral randomisations. We investigated the type I error rate and statistical power of our method based on two real environmental datasets and simulations of tree distributions. Ten types of tree distribution displaying contrasted aggregation properties were simulated, and their abundances were sampled in 153 regularly‐distributed 20 × 20 m quadrats. The SSEF was tested for 1000 simulated tree distributions either unrelated to the environment, or filtered by environmental variables displaying contrasting spatial structures. The method proposed provided a correct type I error rate (< 0.05). The statistical power was high (> 0.9) when abundances were filtered by an environmental variable structured at broad scale. However, the spatial resolution allowed by the sampling design limited the power of the method when using a fine‐scale filtering variable. This highlighted that an ISD can be properly detected providing that the spatial pattern of the filtering process is correctly captured by the sampling design of the study. An R function to apply the SSEF testing method is provided and detailed in a tutorial.