Dataset Information

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species.

ABSTRACT: Glycome in urine could be promising biomarkers for detecting pregnancy diagnosis and sex noninvasively for animals, especially for rare species. We explore the applicability of grouping golden snub-nosed monkeys by sex or diagnosing pregnancy based on their urinary glycopatterns, which are determined via lectin microarray combining mass spectrometry analysis. Sprague-Dawley rats are used to verify whether this approach and whether the glycomic biomarkers can be generalized to other mammalian species. The results show that, for both species, lectin microarray combining mass spectrometry can distinguish individuals' pregnancy status and sex; significant differences are found in the types, amounts, and terminal modification of glycans between pregnant and non-pregnant females and between females and males. This indicates the approach could be generalized to other mammalian species to group sex and detect pregnancy, yet the glycopatterns appear to be species-specific and markers developed from one species may not be directly applicable to another.

SUBMITTER: Yang J

PROVIDER: S-EPMC10783609 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species.

Yang Jiayi J Jin Shiyu S Zhang Simeng S He Shujun S Chen Rui R Lei Yinghu Y Pan Ruliang R Zhang He H Wang Zhongfu Z Li Zheng Z Yu Hanjie H Dong Guixin G Shi Changhong C Li Baoguo B Guo Songtao S

iScience 20231114 12

Glycome in urine could be promising biomarkers for detecting pregnancy diagnosis and sex noninvasively for animals, especially for rare species. We explore the applicability of grouping golden snub-nosed monkeys by sex or diagnosing pregnancy based on their urinary glycopatterns, which are determined via lectin microarray combining mass spectrometry analysis. Sprague-Dawley rats are used to verify whether this approach and whether the glycomic biomarkers can be generalized to other mammalian spe ...[more]

PMID: 38213790

Similar Datasets

Project description:Lung cancer is one of the most prevalent and life-threatening neoplasias worldwide due to the deficiency of ideal diagnostic biomarkers. Although aberrant glycosylation has been observed in human serum and tissue, little is known about the alterations in bronchoalveolar lavage fluid (BALF) that are extremely associated with lung cancer. In this study, our aim was to systematically investigate and assess the alterations of protein glycopatterns in BALF and possibility as biomarkers for diagnosis of lung cancer. Here, lectin microarrays and blotting analysis were utilized to detect the differential expression of BALF glycoproteins from patients with 80 adenocarcinomas (ADC), 77 squamous carcinomas (SCC), 51 small cell lung cancer (SCLC), and 73 benign pulmonary diseases (BPD). These 281 specimens were then randomly divided into a training cohort and validation cohort for constructing and verifying the diagnostic models based on the glycopattern abundances. Moreover, an independent test was performed with 120 newly collected BALF samples enrolled in the double-blind cohort to further assess the clinical application potential of the diagnostic models. According to the results, there were 15 (e.g., PHA-E, EEL, and BPL) and 14 lectins (e.g., PTL-II, LCA, and SJA) that individually showed significant variations in different types and stages of lung cancer compared to BPD. Notably, the diagnostic models achieved better discriminate power in the validation cohort and exhibited high accuracies of 0.917, 0.864, 0.712, 0.671, and 0.781 in the double-blind cohort for the diagnosis of lung cancer, early stage lung cancer, ADC, SCC, and SCLC, respectively. Taken together, the present study revealed that the abnormally altered protein glycopatterns in BALF are expected to be novel potential biomarkers for the identification and early diagnosis of lung cancer, which will contribute to explain the mechanism of the development of lung cancer from the perspective of glycobiology.

Project description:BackgroundThe Neotropics harbors the largest species richness of the planet; however, even in well-studied groups, there are potentially hundreds of species that lack a formal description, and likewise, many already described taxa are difficult to identify using morphology. Specifically in small mammals, complex morphological diagnoses have been facilitated by the use of molecular data, particularly from mitochondrial sequences, to obtain accurate species identifications. Obtaining mitochondrial markers implies the use of PCR and specific primers, which are largely absent for non-model organisms. Oxford Nanopore Technologies (ONT) is a new alternative for sequencing the entire mitochondrial genome without the need for specific primers. Only a limited number of studies have employed exclusively ONT long-reads to assemble mitochondrial genomes, and few studies have yet evaluated the usefulness of such reads in multiple non-model organisms.MethodsWe implemented fieldwork to collect small mammals, including rodents, bats, and marsupials, in five localities in the northern extreme of the Cordillera Central of Colombia. DNA samples were sequenced using the MinION device and Flongle flow cells. Shotgun-sequenced data was used to reconstruct the mitochondrial genome of all the samples. In parallel, using a customized computational pipeline, species-level identifications were obtained based on sequencing raw reads (Whole Genome Sequencing). ONT-based identifications were corroborated using traditional morphological characters and phylogenetic analyses.ResultsA total of 24 individuals from 18 species were collected, morphologically identified, and deposited in the biological collection of Universidad EAFIT. Our different computational pipelines were able to reconstruct mitochondrial genomes from exclusively ONT reads. We obtained three new mitochondrial genomes and eight new molecular mitochondrial sequences for six species. Our species identification pipeline was able to obtain accurate species identifications for up to 75% of the individuals in as little as 5 s. Finally, our phylogenetic analyses corroborated the identifications from our automated species identification pipeline and revealed important contributions to the knowledge of the diversity of Neotropical small mammals.DiscussionThis study was able to evaluate different pipelines to reconstruct mitochondrial genomes from non-model organisms, using exclusively ONT reads, benchmarking these protocols on a multi-species dataset. The proposed methodology can be applied by non-expert taxonomists and has the potential to be implemented in real-time, without the need to euthanize the organisms and under field conditions. Therefore, it stands as a relevant tool to help increase the available data for non-model organisms, and the rate at which researchers can characterize life specially in highly biodiverse places as the Neotropics.

Dataset Information

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species.

Publications

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets