Quantitative Metaproteomics and Activity-based Protein Profiling of Patient Fecal Microbiome Identifies Host and Microbial Serine-type Endopeptidase Activity Associated With Ulcerative Colitis

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but less is known about the molecular effectors of disease. We performed 16S rRNA gene sequencing in parallel with label-free data-dependent LC-MS/MS proteomics to characterize the stool microbiomes of healthy (n = 8) and UC (n = 10) patients. Comparisons of taxonomic composition between techniques revealed major differences in community structure partially attributable to the additional detection of host, fungal, viral, and food peptides by metaproteomics. Differential expression analysis of metaproteomic data identified 176 significantly enriched protein groups between healthy and UC patients. Gene ontology analysis revealed several enriched functions with serine-type endopeptidase activity overrepresented in UC patients. Using a biotinylated fluorophosphonate probe and streptavidin-based enrichment, we show that serine endopeptidases are active in patient fecal samples and that additional putative serine hydrolases are detectable by this approach compared with unenriched profiling. Finally, as metaproteomic databases expand, they are expected to asymptotically approach completeness. Using ComPIL and de novo peptide sequencing, we estimate the size of the probable peptide space unidentified (“dark peptidome”) by our large database approach to establish a rough benchmark for database sufficiency. Despite high variability inherent in patient samples, our analysis yielded a catalog of differentially enriched proteins between healthy and UC fecal proteomes. This catalog provides a clinically relevant jumping-off point for further molecular-level studies aimed at identifying the microbial underpinnings of UC.     

Primary Care Detection of Chronic Kidney Disease in Adults with Type-2 Diabetes: The ADD-CKD Study (Awareness,Detection and Drug Therapy in Type 2 Diabetes and Chronic Kidney Disease)

This US, multicenter, observational study assessed the CKD prevalence in adult patients with type-2 diabetes mellitus (T2DM) and characterized the proportion of detected and undiagnosed CKD in the primary care setting using the following: a clinician survey; a patient physical exam and medical history; a single blood draw for estimated glomerular filtration rate (eGFR) and glycosolated hemoglobin (HbA1c); urine dipstick for protein; urine albumin-creatinine ratio (ACR); two patient quality of life questionnaires; and a 15-month medical record review. The study consisted of 9339 adults with T2DM and 466 investigator sites. Of the 9339 enrolled, 9307 had complete data collection for analysis. The 15-month retrospective review showed urine protein, urine ACR, and eGFR testing were not performed in 51.4%, 52.9% and 15.2% of individuals, respectively. Of the 9307 patients, 5036 (54.1%) had Stage 1–5 CKD based on eGFR and albuminuria; however, only 607 (12.1%) of those patients were identified as having CKD by their clinicians. Clinicians were more successful in diagnosing patients with Stage 3–5 CKD than Stages 1 and 2. There were no differences in clinicians’ likelihood of identification of CKD based on practice setting, number of years in practice, or self-reported patients seen per week. Awareness or patient self-reported CKD was 81.1% with practitioner detection versus 2.6% in the absence of diagnosis. Primary care of T2DM demonstrates recommended urine CKD testing is underutilized, and CKD is significantly under-diagnosed. This is the first study to show CKD detection is associated with awareness.     

Pattern analysis of stem cell differentiation during <Emphasis Type="Italic">in vitro Arabidopsis</Emphasis> organogenesis

Plant somatic cells have the capability to switch their cell fates from differentiated to undifferentiated status under proper culture conditions, which is designated as totipotency. As a result, plant cells can easily regenerate new tissues or organs from a wide variety of explants. However, the mechanism by which plant cells have such remarkable regeneration ability is still largely unknown. In this study, we used a set of meristem-specific marker genes to analyze the patterns of stem cell differentiation in the processes of somatic embryogenesis as well as shoot or root organogenesis in vitro. Our studies furnish preliminary and important information on the patterns of the de novo stem cell differentiation during various types of in vitro organogenesis.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Radial astrocytes and ependymocytes in the spinal cord of the adult toad (Bufo bufo L.)

Summary Immunohistochemical and ultrastructural techniques have been used to demonstrate glial fibrillary acidic protein (GFAP) immuno-positive cells in the adult toad spinal cord. Two types of GFAP-immunoreactive cells were observed: ependymocytes and radial astrocytes. GFAP-positive ependymocytes were scarce and contained the immunoreactive product in their processes. They showed intermediate filaments in the basal pole and in their processes when studied with the electron microscope. These immuno-positive ependymocytes represent the tanycytic form of ependymal cells because their processes ended at the subpial zone. The radial astrocytes showed a more intensive immunoreactive product in somata and processes when they were located far away from the ependymal layer. Cell bodies and processes were also associated with blood vessels, but most of the processes ended at the subpial zone forming a continuous subpial glia limitans. The GFAP-positive processes, which form this subpial glia limitans in the toad spinal cord, belong to both tanycytic ependymocytes and radial astrocytes, whose somata are located in the grey matter. These findings lead us to suggest that both types of GFAP-immunopositive cells might be the functional equivalents of mammalian astrocytes.     

Urban Household Carbon Emission and Contributing Factors in the Yangtze River Delta,China

Carbon reduction at the household level is an integral part of carbon mitigation. This study analyses the characteristics, effects, contributing factors and policies for urban household carbon emissions in the Yangtze River Delta of China. Primary data was collected through structured questionnaire surveys in three cities in the region – Nanjing, Ningbo, and Changzhou in 2011. The survey data was first used to estimate the magnitude of household carbon emissions in different urban contexts. It then examined how, and to what extent, each set of demographic, economic, behavioral/cognitive and spatial factors influence carbon emissions at the household level. The average of urban household carbon emissions in the region was estimated to be 5.96 tonnes CO₂ in 2010. Energy consumption, daily commuting, garbage disposal and long-distance travel accounted for 51.2%, 21.3%, 16.0% and 11.5% of the total emission, respectively. Regulating rapidly growing car-holdings of urban households, stabilizing population growth, and transiting residents’ low-carbon awareness to household behavior in energy saving and other spheres of consumption in the context of rapid population aging and the growing middle income class are suggested as critical measures for carbon mitigation among urban households in the Yangtze River Delta.     

Intravenous injection of the oncolytic virus M1 awakens antitumor T cells and overcomes resistance to checkpoint blockade

Reversing the highly immunosuppressive tumor microenvironment (TME) is essential to achieve long-term efficacy with cancer immunotherapy. Despite the impressive clinical response to checkpoint blockade in multiple types of cancer, only a minority of patients benefit from this approach. Here, we report that the oncolytic virus M1 induces immunogenic tumor cell death and subsequently restores the ability of dendritic cells to prime antitumor T cells. Intravenous injection of M1 disrupts immune tolerance in the privileged TME, reprogramming immune-silent (cold) tumors into immune-inflamed (hot) tumors. M1 elicits potent CD8⁺ T cell-dependent therapeutic effects and establishes long-term antitumor immune memory in poorly immunogenic tumor models. Pretreatment with M1 sensitizes refractory tumors to subsequent checkpoint blockade by boosting T-cell recruitment and upregulating the expression of PD-L1. These findings reveal the antitumor immunological mechanism of the M1 virus and indicated that oncolytic viruses are ideal cotreatments for checkpoint blockade immunotherapy.Subject terms: Cancer microenvironment, Targeted therapies     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.