Amy M. Paten

ORCID: 0000-0003-0420-2155
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About
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Research Areas
  • Reproductive Physiology in Livestock
  • Birth, Development, and Health
  • Genetic and phenotypic traits in livestock
  • Microbial Metabolic Engineering and Bioproduction
  • Insect and Arachnid Ecology and Behavior
  • Animal Genetics and Reproduction
  • Plant and animal studies
  • Insect and Pesticide Research
  • Molecular Biology Techniques and Applications
  • Bioinformatics and Genomic Networks
  • Milk Quality and Mastitis in Dairy Cows
  • Biofuel production and bioconversion
  • Metabolomics and Mass Spectrometry Studies
  • Cancer Cells and Metastasis
  • Per- and polyfluoroalkyl substances research
  • Analytical Chemistry and Chromatography
  • Effects and risks of endocrine disrupting chemicals
  • Agriculture Sustainability and Environmental Impact
  • Toxic Organic Pollutants Impact
  • Isotope Analysis in Ecology
  • Gut microbiota and health
  • RNA Research and Splicing
  • Assisted Reproductive Technology and Twin Pregnancy
  • Infant Nutrition and Health
  • RNA modifications and cancer

Commonwealth Scientific and Industrial Research Organisation
2019-2024

CSIRO Health and Biosecurity
2024

CSIRO Land and Water
2019-2022

Health Sciences and Nutrition
2019

Massey University
2011-2016

University of Otago
2014-2015

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets life science. Omics provide a more holistic molecular perspective studied biological systems compared to traditional approaches. However, due their inherent data differences, integrating platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products interactions between genes, transcripts, proteins,...

10.3390/metabo9040076 article EN cc-by Metabolites 2019-04-18

Abstract Microbiomes are foundational components of the environment that provide essential services relating to food security, carbon sequestration, human health, and overall well-being ecosystems. Microbiota exert their effects primarily through complex interactions at interfaces with plant, animal, hosts, as well within soil environment. This review aims explore ecological, evolutionary, molecular processes governing establishment function microbiome–host relationships, specifically...

10.1093/femsre/fuae008 article EN cc-by-nc FEMS Microbiology Reviews 2024-02-28

10.1016/j.scitotenv.2019.04.402 article EN publisher-specific-oa The Science of The Total Environment 2019-04-28

The mammary gland is a dynamic organ that undergoes dramatic physiological adaptations during the transition from late pregnancy to lactation. Investigation of molecular basis development and function will provide fundamental insights into tissue remodelling as well better understanding milk production disease. This important livestock systems human health. Here we use RNA-seq identify differences in gene expression ovine between Between (135 days gestation ± 2.4 SD) lactation (15 post...

10.1186/s12864-015-1947-9 article EN cc-by BMC Genomics 2015-10-05

Studies using sheep models indicate that the fetal mammary gland is sensitive to maternal nutrition during gestation; however, results have been inconsistent and do not identify critical feeding periods. This study aimed clarify previous findings by partitioning period of nutritional manipulation into 2 stages: early mid-to-late pregnancy. Sixty-six twin-born, twin-bearing ewes, born dams were fed either submaintenance, maintenance, or ad libitum pregnancy (d 21 50 pregnancy; SmP21–50,...

10.2527/jas.2012-5752 article EN Journal of Animal Science 2012-12-11

The mammary gland is a complex tissue consisting of multiple cell types which, over the lifetime an animal, go through repeated cycles development associated with pregnancy, lactation and involution. also known to be sensitive maternal programming by environmental stimuli such as nutrition. molecular basis these adaptations significant interest, but requires robust methods measure gene expression. Reverse-transcription quantitative PCR (RT-qPCR) commonly used expression, currently method...

10.1152/physiolgenomics.00030.2014 article EN Physiological Genomics 2014-06-04

Abstract Introduction Nuclear magnetic resonance (NMR) is widely used in metabolomics but it focusses on 1 H over other NMR-active nuclei. Objectives To evaluate the potential of alternative NMR-sensitive nuclei to generate useful metabolomic data. Method Proton, carbon, phosphorus, and nitrogen-based NMR was undertaken extracts from mint European honey bee tissue. Results Carbon provided information required larger sample sizes. Phosphorus produced overlapping peaks one dimensional (1D)...

10.1007/s11306-023-02003-z article EN cc-by Metabolomics 2023-04-15

Understanding the cumulative risk of chemical mixtures at environmentally realistic concentrations is a key challenge in honey bee ecotoxicology. Ecotoxicogenomics, including transcriptomics, measures responses individual organisms molecular level which can provide insights into mechanisms underlying phenotypic induced by one or more stressors and link impacts on individuals to populations. Here, fifth instar larvae were sampled from previously reported field experiment exploring chronic...

10.1016/j.scitotenv.2021.152614 article EN cc-by-nc-nd The Science of The Total Environment 2021-12-25

The foetal mammary gland is sensitive to maternal weight and nutrition during gestation, which could affect offspring milk production. It has previously been shown that ewes born dams offered maintenance pregnancy (day 21 140 of gestation) produced greater milk, lactose CP yields in their first lactation when compared with ad libitum nutrition. In addition, heavier lighter dams. objective this study was analyse compare the 5-year performance mentioned ewes, heavy or light were Ewes milked...

10.1017/s175173111600241x article EN cc-by-nc-nd animal 2016-11-21

Abstract Genome-scale metabolic models (GEMs) are essential tools in systems and synthetic biology, enabling the mathematical simulation of pathways encoded genomes to predict phenotypes. The complexity GEMs, however, can often limit interpretation comparison their outputs. Here, we present MMINT (Metabolic Modelling Interactive Network Tool), designed facilitate exploration networks. employs GEM networks flux solutions derived from Constraint Based Analysis (e.g. Flux Balance Analysis)...

10.1101/2024.08.06.606923 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2024-08-07
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