=Paper=
{{Paper
|id=Vol-3603/workshopOIIDDS3
|storemode=property
|title=Multi-Ontology framework of Maternal Milk for Immune Systems (MOMMIS)
|pdfUrl=https://ceur-ws.org/Vol-3603/workshopOIIDDS3.pdf
|volume=Vol-3603
|authors=Emily Steliotes,Daniela Barile,Matthew Lange
|dblpUrl=https://dblp.org/rec/conf/icbo/SteliotesBL23
}}
==Multi-Ontology framework of Maternal Milk for Immune Systems (MOMMIS) ==
https://ceur-ws.org/Vol-3603/workshopOIIDDS3.pdf
Multi-Ontology framework of Maternal Milk for Immune Systems
(MOMMIS) - Extended Abstract
Emily Steliotes 1,2, Daniela Barile1 and Matthew Lange 2
1
University of California, Davis, Department of Food Science and Technology, One Shields Ave, Davis, CA, USA
2
International Center for Food Ontology Operability Data and Semantics (IC-FOODS), 216 F St, Suite #139 Davis,
CA, USA
Abstract
We propose a multi-ontology framework modeling the impacts of milk composition on immune
health outcomes, using maternal milk as a case study. We evaluated the wide array of immune-
health promoting bioactive factors in mammalian milk and existing ontologies relevant to food,
nutrition, and health. From here, we are aligning existing ontologies and developing new ontologies
to fill notable gaps. MilkOligoDB, which allows for the comparison of milk oligosaccharide
profiles among mammalian species and across the literature, demonstrates how the MOMMIS
framework can be instantiated. MOMMIS will be useful for interdisciplinary and translational
research at the intersection of food and health science disciplines.
Keywords 1
Maternal Milk, Milk Composition, Immune Systems, Immune Health, Ontologies
1. Immune Health vs. Immune Disease
Neonatal immune cells, with little immunological memory, a developing immune system, and
increased vulnerability to a vast array of infectious and non-infectious diseases and conditions, must
simultaneously mount responses against environmental stimuli while maturing (1–3). Establishment,
development, maturation, optimization and maintenance of immune system functions leads to improved
disease resistance, healthspan, and longevity (4,5). Current immune system ontological structures
annotate immune system components relative to their corresponding disease states and drug treatments
(6,7). Ontological structures are needed, which are capable of annotating immune health system
development, maturation, and improvement including both intrinsic and extrinsic factors.
2. Development of Ontologies at the Intersection of Milk Composition and
Immune Health
Maternal milk provides the perfect case study to ontologically model food composition impacts on
immune health. As mammals’ first food, milk confers health from one generation to the next in ways that
no other food or biological fluid does. Transmitting evolutionary knowledge via milk, mothers catabolize
their own bodies to create and deliver a food providing everything an infant needs, and nothing more.
Maternal milk is the only substance consumed through the course of a mammal's lifetime informed by
millenia of Darwinian selective pressure to nourish and improve the immune system of its consumer while
also setting the stage for improved healthspan and disease resistance (8,9). Children need milk for bone
growth, and infants rely on it for crucial immune function as they develop (10,11).
Proceedings of the International Conference on Biomedical Ontologies 2023, August 28th-September 1st, 2023, Brasilia, Brazil
EMAIL: esteliotes@ucdavis.edu (Emily Steliotes); dbarile@ucdavis.edu (Daniela Barile); matthew@ic-foods.org (Matthew Lange)
ORCID: 0009-0006-0501-880X (Emily Steliotes); 0000-0002-3889-1596 (Daniela Barile); 0000-0002-6148-7962 (Matthew Lange)
©️ 2023 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
199
Annotating milk is a worthwhile pursuit because milk plays a crucial role in the growth and development
of mammals. An ontologically based maternal milk ⇔ infant health informatics framework offers the
opportunity to links bodily tissues and fluids, as well as their packaging and delivery into nutritive foods
with the metabolic processes and health outcomes of the consuming organism. Specifically relating to
organismal immunological function, ontologically modeling maternal milk and its consumption affords the
opportunity to better understand establishment, development, maturation, optimization and maintenance
of immune system functions across molecular, cellular, organ, and systems levels. It will also be crucial for
interdisciplinary translational research efforts, i.e. determining how an increase in oligosaccharide content
in milk affects immune-mediated health outcomes or what immune health-promoting bioactive factor(s)
affect the development and/or treatment of emerging viruses such as COVID-19.
2.1. Mammalian Milk Immune Components
Mammalian milk contains a variety of immune-health promoting bioactive factors (milk immune
components) including but not limited to: hormones, cytokines, chemokines, lymphocytes, macrophages,
neutrophils, T cells, immunoglobulins, lactoferrin, lysozyme, bioactive peptides, antibodies, stem cells,
human milk oligosaccharides (HMOs), the microbiota, and microRNAs capable of the mechanisms by
which they drive immune maturation (11,12). For example, HMOs play an important role in the
prevention of necrotizing enterocolitis, a disease occurring in sick or premature babies (13)(14).
Bifidobacteria infantis, a probiotic that grows selectively on specific HMOs, is currently used to treat
necrotizing enterocolitis (15).
2.1.1. Existing food, nutrition, and health ontologies related to milk immune
components
Annotating maternal milk components for their relationships to immune health using ontologies lays
the groundwork for a comprehensive food, nutrition, and health informatics framework describing any
food components and their corresponding immune health outcomes. Connecting multiple ontologies by
building multi-ontology food informatics frameworks allows researchers to ask and answer more
interdisciplinary questions (16–19). The Multi-Ontology framework of Maternal Milk for Immune
Systems (MOMMIS) connects the following biological ontologies: FoodOn (20), Uberon (21),
Compositional Dietary Nutrition Ontology (CDNO) (17), the Mass spectrometry ontology (HUPO) (22),
the Mammalian phenotype ontology (23), and the Gene Ontology (GO) (6). Ontologies related to
nutrition interventions and personalized nutrition experiments will also be crucial. These include but are
not limited to: the Ontology of Precision Medicine and Investigation (OPMI) (24), the Ontology for
Biomedical Investigations (OBI) (25), the Ontology for Nutritional Epidemiology (ONE) (26), the
Ontology for Nutritional Studies (ONS) (27), the Food Biomarker Ontology (FOBI) (28), the Human
Disease Ontology (DO) (29), and the Medical Action Ontology (MaXO) (7), and the Ontology of Host-
Microbiome Interactions (OHMI) (30).
2.1.2. Connecting UC Milk and MilkOligoDB: Oligosaccharides as key milk immune
components
UC Milk is an ontology that was developed to characterize mammalian milk components and the
biological processes giving rise to their creation. The ontology describes both the production and
processing of milk itself as well as the role of milk throughout the life cycle, including during three key
stages: infant, pregnancy, and lactation (31). MilkOligoDB allows for the comparison of milk
oligosaccharide profiles among mammalian species and across the literature. It demonstrates the
considerable variation in oligosaccharide profiles both between species and within species (32). Building
off of the data model for MilkOligoDB (32), we extend CheBI oligosaccharide classes to cover known
classes of mammalian oligosaccharides and then instantiate these classes in the oligosaccharide class
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(prebiotics) to probiotics in the gut that confer immunological health benefits, including for different
types of mammalian milks. Ontologies that allow us to model milk processing conditions such as
pasteurization, which are especially relevant for mothers who cannot breastfeed, are being built as well
(33).
3. Acknowledgements
We are grateful to the US National Science Foundation, NSF Award numbers RCN 1737573 OAC
2112606, for funding this research and the conceptualization and editing of this Special Collection, both of
which were underpinned by our NSF-funded Research Coordination Network, “Developing Informational
Infrastructure for Building Smart Regional Foodsheds”.
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4. References
[1] Gollwitzer ES, Marsland BJ. Impact of Early-Life Exposures on Immune Maturation and
Susceptibility to Disease. Trends Immunol. 2015 Nov;36(11):684–96.
[2] Basha S, Surendran N, Pichichero M. Immune responses in neonates. Expert Rev Clin Immunol. 2014
Sep;10(9):1171–84.
[3] Yu JC, Khodadadi H, Malik A, Davidson B, Salles É da SL, Bhatia J, et al. Innate Immunity of
Neonates and Infants. Front Immunol. 2018 Jul 30;9:1759.
[4] Chaplin DD. Overview of the immune response. J Allergy Clin Immunol. 2010 Feb;125(2 Suppl
2):S3–23.
[5] Ji S, Xiong M, Chen H, Liu Y, Zhou L, Hong Y, et al. Cellular rejuvenation: molecular mechanisms
and potential therapeutic interventions for diseases. Signal Transduction and Targeted Therapy. 2023
Mar 14;8(1):1–39.
[6] Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the
unification of biology. The Gene Ontology Consortium. Nat Genet. 2000 May;25(1):25–9.
[7] Carmody LC, Gargano MA, Toro S, Vasilevsky NA, Adam MP, Blau H, et al. The Medical Action
Ontology: A Tool for Annotating and Analyzing Treatments and Clinical Management of Human
Disease. medRxiv [Internet]. 2023 Jul 13; Available from:
http://dx.doi.org/10.1101/2023.07.13.23292612
[8] J. Bruce German FLS. International milk genomics consortium. Trends Food Sci Technol.
2006;(12):656–61.
[9] Sela DA, Mills DA. The marriage of nutrigenomics with the microbiome: the case of infant-associated
bifidobacteria and milk. Am J Clin Nutr. 2014 Mar;99(3):697S – 703S.
[10] Carr LE, Virmani MD, Rosa F, Munblit D, Matazel KS, Elolimy AA, et al. Role of Human Milk
Bioactives on Infants’ Gut and Immune Health. Front Immunol. 2021 Feb 12;12:604080.
[11] Ballard O, Morrow AL. Human milk composition: nutrients and bioactive factors. Pediatr Clin North
Am. 2013 Feb;60(1):49–74.
[12] Sampath V, Martinez M, Caplan M, Underwood MA, Cuna A. Necrotizing enterocolitis in premature
infants-A defect in the brakes? Evidence from clinical and animal studies. Mucosal Immunol. 2023
Apr;16(2):208–20.
[13] Bode L. Human Milk Oligosaccharides in the Prevention of Necrotizing Enterocolitis: A Journey From
in vitro and in vivo Models to Mother-Infant Cohort Studies. Front Pediatr. 2018 Dec 4;6:385.
[14] Tobias J, Olyaei A, Laraway B, Jordan BK, Dickinson SL, Golzarri-Arroyo L, et al.
Bifidobacteriumlongum subsp. infantis EVC001 Administration Is Associated with a Significant
Reduction in the Incidence of Necrotizing Enterocolitis in Very Low Birth Weight Infants. J Pediatr.
2022 May;244:64–71.e2.
[15] Lange MC, Lemay DG. A multi‐ontology framework to guide agriculture and food towards diet and
health. of the Science of Food and … [Internet]. 2007; Available from:
https://onlinelibrary.wiley.com/doi/abs/10.1002/jsfa.2832
[16] Andrés-Hernández L, Blumberg K, Walls RL, Dooley D, Mauleon R, Lange M, et al. Establishing a
Common Nutritional Vocabulary - From Food Production to Diet. Front Nutr. 2022 Jun 21;9:928837.
[17] Dooley D, Andrés-Hernández L, Bordea G, Carmody L, Cavalieri D, Chan L, et al. OBO Foundry
Food Ontology Interconnectivity [Internet]. [cited 2023 Jul 18]. Available from:
https://www.semantic-web-journal.net/system/files/swj3458.pdf
[18] Tomich TP, Hoy C, Dimock MR, Hollander AD, Huber PR, Hyder A, et al. Why Do We Need Food
Systems Informatics? Introduction to This Special Collection on Smart and Connected Regional Food
Systems. Sustain Sci Pract Policy. 2023 Apr 12;15(8):6556.
[19] Dooley DM, Griffiths EJ, Gosal GS, Buttigieg PL, Hoehndorf R, Lange MC, et al. FoodOn: a
harmonized food ontology to increase global food traceability, quality control and data integration.
NPJ Sci Food. 2018 Dec 18;2:23.
202
[20] Mungall CJ, Torniai C, Gkoutos GV, Lewis SE, Haendel MA. Uberon, an integrative multi-species
anatomy ontology. Genome Biol. 2012 Jan 31;13(1):R5.
[21] Mayer G, Montecchi-Palazzi L, Ovelleiro D, Jones AR, Binz PA, Deutsch EW, et al. The HUPO
proteomics standards initiative- mass spectrometry controlled vocabulary. Database . 2013 Mar
12;2013:bat009.
[22] Smith CL, Eppig JT. The Mammalian Phenotype Ontology as a unifying standard for experimental
and high-throughput phenotyping data. Mamm Genome. 2012 Oct;23(9-10):653–68.
[23] opmi: OPMI: Ontology of Precision Medicine and Investigation [Internet]. Github; [cited 2023 Aug
3]. Available from: https://github.com/OPMI/opmi
[24] Bandrowski A, Brinkman R, Brochhausen M, Brush MH, Bug B, Chibucos MC, et al. The Ontology
for Biomedical Investigations. PLoS One. 2016 Apr 29;11(4):e0154556.
[25] Yang C, Ambayo H, Baets BD, Kolsteren P, Thanintorn N, Hawwash D, et al. An Ontology to
Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked
Content. Nutrients [Internet]. 2019 Jun 8;11(6). Available from:
http://dx.doi.org/10.3390/nu11061300
[26] Vitali F, Lombardo R, Rivero D, Mattivi F, Franceschi P, Bordoni A, et al. ONS: an ontology for a
standardized description of interventions and observational studies in nutrition. Genes Nutr. 2018 Apr
30;13:12.
[27] Castellano-Escuder P, González-Domínguez R, Wishart DS, Andrés-Lacueva C, Sánchez-Pla A.
FOBI: an ontology to represent food intake data and associate it with metabolomic data. Database
[Internet]. 2020 Jan 1;2020. Available from: http://dx.doi.org/10.1093/databa/baaa033
[28] Schriml LM, Munro JB, Schor M, Olley D, McCracken C, Felix V, et al. The Human Disease Ontology
2022 update. Nucleic Acids Res. 2022 Jan 7;50(D1):D1255–61.
[29] He Y, Wang H, Zheng J, Beiting DP, Masci AM, Yu H, et al. OHMI: the ontology of host-microbiome
interactions. J Biomed Semantics. 2019 Dec 30;10(1):25.
[30] Colet E, Lange M. uc_Milk: An Ontology for Scientifically-based Unambiguous Characterization of
Mammalian Milk, their Composition and the Biological Processes Giving Rise to their Creation. In:
ICBO/BioCreative [Internet]. Citeseer; 2016. Available from:
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=d04a08822664808ed01fe62204ab
1b36b7c047fe
[31] Durham SD, Wei Z, Lemay DG, Lange MC, Barile D. Creation of a milk oligosaccharide database,
MilkOligoDB, reveals common structural motifs and extensive diversity across mammals. Sci Rep.
2023 Jun 26;13(1):10345.
[32] Salcedo J, Karav S, Le Parc A, Cohen JL, de Moura Bell JMLN, Sun A, et al. Application of industrial
treatments to donor human milk: influence of pasteurization treatments, storage temperature, and time
on human milk gangliosides. NPJ Sci Food. 2018 Mar 13;2:5.
203