Project description:Eukaryotic cells use microtubule-based intracellular transport for the delivery of many subcellular cargos, including organelles. The canonical view of organelle transport is that organelles directly recruit molecular motors via cargo-specific adaptors. In contrast with this view, we show here that peroxisomes move by hitchhiking on early endosomes, an organelle that directly recruits the transport machinery. Using the filamentous fungus Aspergillus nidulans we found that hitchhiking is mediated by a novel endosome-associated linker protein, PxdA. PxdA is required for normal distribution and long-range movement of peroxisomes, but not early endosomes or nuclei. Using simultaneous time-lapse imaging, we find that early endosome-associated PxdA localizes to the leading edge of moving peroxisomes. We identify a coiled-coil region within PxdA that is necessary and sufficient for early endosome localization and peroxisome distribution and motility. These results present a new mechanism of microtubule-based organelle transport in which peroxisomes hitchhike on early endosomes and identify PxdA as the novel linker protein required for this coupling.
Project description:Primary outcome(s): Comparison of diagnostic accuracy of urinary protein fragments and carcinoembryonic antigen (CEA) for adenocarcinoma (gastric cancer, colorectal cancer, or bile duct cancer)
Project description:This study was designed to address key questions concerning the use of alternative protein sources for animal feeds and addresses aspects such as their nutrient composition and impact on gut function. We used casein (CAS), spray dried porcine plasma (SDPP), soybean meal (SBM), and yellow meal worm (YMW) as protein sources. We have investigated the use of intestinal organoids as a model to test the effects of different protein sources on the intestinal epithelium. Mouse enteroids were exposed to different undigested protein sources (4% w/v, viz. soybean meal, SBM; casein, CAS; spray dried plasma protein, SDPP; and yellow meal worm, YMW) or DMEM as a control. Microarrays were used to detail the global gene expression.
Project description:Early diagnosis of brain tumours is challenging and a major unmet need. Patients with brain tumours most often present with non-specific symptoms more commonly associated with less serious diagnoses, making it difficult to determine which patients to prioritize for brain imaging. Delays in diagnosis affect timely access to treatment, with potential impacts on quality of life and survival. A test to help identify which patients with non-specific symptoms are most likely to have a brain tumour at an earlier stage would dramatically impact on patients by prioritizing demand on diagnostic imaging facilities. This clinical feasibility study of brain tumour early diagnosis was aimed at determining the accuracy of our novel spectroscopic liquid biopsy test for the triage of patients with non-specific symptoms that might be indicative of a brain tumour, for brain imaging. Patients with a suspected brain tumour based on assessment of their symptoms in primary care can be referred for open access CT scanning. Blood samples were prospectively obtained from 385 of such patients, or patients with a new brain tumour diagnosis. Samples were analysed using our spectroscopic liquid biopsy test to predict presence of disease, blinded to the brain imaging findings. The results were compared to the patient's index brain imaging delivered as per standard care. Our test predicted the presence of glioblastoma, the most common and aggressive brain tumour, with 91% sensitivity, and all brain tumours with 81% sensitivity, and 80% specificity. Negative predictive value was 95% and positive predictive value 45%. The reported levels of diagnostic accuracy presented here have the potential to improve current symptom-based referral guidelines, and streamline assessment and diagnosis of symptomatic patients with a suspected brain tumour.
Project description:Salmonid resources currently foster socioeconomic prosperity in several nations, yet their importance to many ancient circumpolar societies is poorly understood due to insufficient fish bone preservation at archaeological sites. As a result, there are serious gaps in our knowledge concerning the antiquity of northern salmonid fisheries and their impacts on shaping biodiversity, hunter-gatherer adaptations, and human-ecological networks. The interdisciplinary study presented here demonstrates that calcium-magnesium phosphate minerals formed in burned salmonid bones can preserve at ancient northern sites, thus informing on the early utilization of these resources despite the absence of morphologically classifiable bones. The minerals whitlockite and beta magnesium tricalcium phosphate were identified in rare morphologically classifiable Atlantic salmonid bones from three Mid-Holocene sites in Finland. Large amounts of beta magnesium tricalcium phosphate were also experimentally formed by burning modern Atlantic salmonid and brown trout bones. Our results demonstrate the value of these minerals as proxies for ancient northern salmonid fishing. Specifically, the whitlockite mineral was discovered in hearth sediments from the 5,600 year old Yli-Ii Kierikinkangas site on the Iijoki River in northern Finland. Our fine sieving and mineralogical analyses of these sediments, along with zooarchaeological identification of recovered bone fragments, have confirmed for the first time that the people living at this village did incorporate salmonids into their economies, thus providing new evidence for early estuary/riverine fisheries in northern Finland.
Project description:BackgroundWith the goal of discovering non-invasive biomarkers for early diagnosis of GC, we conducted a case-control study utilising urine samples from individuals with predominantly early GC vs. healthy control (HC).MethodsAmong urine samples from 372 patients, age- and sex-matched 282 patients were randomly divided into three groups: 18 patients in a discovery cohort; 176 patients in a training cohort and 88 patients in a validation cohort.ResultsAmong urinary proteins identified in the comprehensive quantitative proteomics analysis, urinary levels of TFF1 (uTFF1) and ADAM12 (uADAM12) were significantly independent diagnostic biomarkers for GC, in addition to Helicobacter pylori status. A urinary biomarker panel combining uTFF1, uADAM12 and H. pylori significantly distinguished between HC and GC patients in both training and validation cohorts. On the analysis for sex-specific biomarkers, this combination panel demonstrated a good AUC of 0.858 for male GC, whereas another combination panel of uTFF1, uBARD1 and H. pylori also provided a good AUC of 0.893 for female GC. Notably, each panel could distinguish even stage I GC patients from HC patients (AUC = 0.850 for males; AUC = 0.845 for females).ConclusionsNovel urinary protein biomarker panels represent promising non-invasive biomarkers for GC, including early-stage disease.
Project description:Accurate and comprehensive genomic annotation, including the full list of protein-coding genes, is vital for understanding the molecular mechanisms of human biology. We have previously shown that the genome contains a multitude of yet hidden functional exons and transcripts, some of which might represent novel mRNAs. These results resonate with those from other groups and strongly argue that two decades after the completion of the first draft of the human genome sequence, the current annotation of human genes and transcripts remains far from being complete. Using a targeted RNA enrichment technique, we showed that one of the novel functional exons previously discovered by us and currently annotated as part of a long non-coding RNA, is actually a part of a novel protein-coding gene, InSETG-4, which encodes a novel human protein with no known homologs or motifs. We found that InSETG-4 is induced by various DNA-damaging agents across multiple cell types and therefore might represent a novel component of DNA damage response. Despite its low abundance in bulk cell populations, InSETG-4 exhibited expression restricted to a small fraction of cells, as demonstrated by the amplification-based single-molecule fluorescence in situ hybridization (asmFISH) analysis. This study argues that yet undiscovered human protein-coding genes exist and provides an example of how targeted RNA enrichment techniques can help to fill this major gap in our knowledge of the information encoded in the human genome.
Project description:BACKGROUND: Construction of a reliable network remains the bottleneck for network-based protein function prediction. We built an artificial network model called protein overlap network (PON) for the entire genome of yeast, fly, worm, and human, respectively. Each node of the network represents a protein, and two proteins are connected if they share a domain according to InterPro database. RESULTS: The function of a protein can be predicted by counting the occurrence frequency of GO (gene ontology) terms associated with domains of direct neighbors. The average success rate and coverage were 34.3% and 43.9%, respectively, for the test genomes, and were increased to 37.9% and 51.3% when a composite PON of the four species was used for the prediction. As a comparison, the success rate was 7.0% in the random control procedure. We also made predictions with GO term annotations of the second layer nodes using the composite network and obtained an impressive success rate (>30%) and coverage (>30%), even for small genomes. Further improvement was achieved by statistical analysis of manually annotated GO terms for each neighboring protein. CONCLUSIONS: The PONs are composed of dense modules accompanied by a few long distance connections. Based on the PONs, we developed multiple approaches effective for protein function prediction.
Project description:Ovarian cancer (OC) has the highest mortality of all gynaecological cancers. Early diagnosis offers an approach to achieving better outcomes. We conducted a blinded-evaluation of prospectively collected preclinical serum from participants in the multimodal group of the United Kingdom Collaborative Trial of Ovarian Cancer Screening. Using isobaric tags (iTRAQ) we identified 90 proteins differentially expressed between OC cases and controls. A second targeted mass spectrometry analysis of twenty of these candidates identified Protein Z as a potential early detection biomarker for OC. This was further validated by ELISA analysis in 482 serial serum samples, from 80 individuals, 49 OC cases and 31 controls, spanning up to 7 years prior to diagnosis. Protein Z was significantly down-regulated up to 2 years pre-diagnosis (p = 0.000000411) in 8 of 19 Type I patients whilst in 5 Type II individuals, it was significantly up-regulated up to 4 years before diagnosis (p = 0.01). ROC curve analysis for CA-125 and CA-125 combined with Protein Z showed a statistically significant (p = 0.00033) increase in the AUC from 77 to 81% for Type I and a statistically significant (p= 0.00003) increase in the AUC from 76 to 82% for Type II. Protein Z is a novel independent early detection biomarker for Type I and Type II ovarian cancer; which can discriminate between both types. Protein Z also adds to CA-125 and potentially the Risk of Ovarian Cancer algorithm in the detection of both subtypes.
Project description:Protein family databases are an important tool for biologists trying to dissect the function of proteins. Comparing potential new families to the thousands of existing entries is an important task when operating a protein family database. This comparison helps to understand whether a collection of protein regions forms a novel family or has overlaps with existing families of proteins. In this paper, we describe a method for performing this analysis with an adjustable level of accuracy, depending on the desired speed, enabling interactive comparisons. This method is based upon the MinHash algorithm, which we have further extended to calculate the Jaccard containment rather than the Jaccard index of the original MinHash technique. Testing this method with the Pfam protein family database, we are able to compare potential new families to the over 17,000 existing families in Pfam in less than a second, with little loss in accuracy.