Chastant-Maillard, S. et al. Reproductive efficiency and pre-weaning mortality: Preliminary evaluation of 27,221 purebred feminine dogs and 204,537 puppies in France. Reprod. Domest. Anim. 52, 158–162 (2017).
Indrebø, A., Trangerud, C. & Moe, L. Canine neonatal mortality in 4 giant breeds. Acta Vet. Scand. 49, S2 (2007).
Mugnier, A. et al. Birth weight as a danger issue for neonatal mortality: Breed-specific strategy to determine at-risk puppies. Prev. Vet. Med. 171, 104746 (2019).
Groppetti, D., Ravasio, G., Bronzo, V. & Pecile, A. The position of start weight on litter dimension and mortality inside 24h of life in purebred dogs: What points are concerned?. Anim. Reprod. Sci. 163, 112–119 (2015).
Mila, H. et al. Immunoglobulin G focus in canine colostrum: Evaluation and variability. J. Reprod. Immunol. 112, 24–28 (2015).
Sender, R., Fuchs, S. & Milo, R. Revised estimates for the variety of human and micro organism cells within the physique. PLoS Biol. 14, e1002533 (2016).
Suchodolski, J. S. Intestinal microbiota of dogs and cats: An even bigger world than we thought. Vet. Clin. N. Am. Small Anim. Pract. 41, 261–272 (2011).
Henderickx, J. G. E. et al. Maturation of the preterm gastrointestinal tract may be outlined by host and microbial markers for digestion and barrier protection. Sci. Rep. 11, 12808 (2021).
Pammi, M. et al. Intestinal dysbiosis in preterm infants previous necrotizing enterocolitis: A scientific evaluate and meta-analysis. Microbiome 5, 31 (2017).
Cox, L. M. et al. Altering the intestinal microbiota throughout a vital developmental window has lasting metabolic penalties. Cell 158, 705–721 (2014).
Kostic, A. D. et al. The dynamics of the human toddler intestine microbiome in growth and in development towards sort 1 diabetes. Cell Host Microbe 17, 260–273 (2015).
Unger, S., Stintzi, A., Shah, P., Mack, D. & O’Connor, D. L. Gut microbiota of the very-low-birth-weight toddler. Pediatr. Res. 77, 205–213 (2015).
Li, N. et al. Characterization of the youth microbiota growth and predominant Lactobacillus species at distinct intestine segments of low- and normal-birth-weight piglets. Front. Microbiol. 10, 797 (2019).
Huang, S.-M. et al. Perturbation of the lipid metabolism and intestinal irritation in rising pigs with low start weight is related to the alterations of intestine microbiota. Sci. Total Environ. 719, 137382 (2020).
Cai, C. et al. Feeding apply influences intestine microbiome composition in very low start weight preterm infants and the affiliation with oxidative stress: A potential cohort research. Free Radic. Biol. Med. 142, 146–154 (2019).
Guard, B. C. et al. Characterization of the fecal microbiome throughout neonatal and early pediatric growth in puppies. PLoS ONE 12, e0175718 (2017).
Del Carro, A. et al. The evolution of dam-litter microbial flora from start to 60 days of age. BMC Vet. Res. 18, 95 (2022).
Masuoka, H. et al. Transition of the intestinal microbiota of dogs with age. Biosci. Microbiota Food Health 36, 27–31 (2017).
Saladrigas-García, M. et al. An perception into the business piglet’s microbial intestine colonization: From start in the direction of weaning. Anim. Microbiome 4, 68 (2022).
Hill, C. J. et al. Evolution of intestine microbiota composition from start to 24 weeks within the INFANTMET Cohort. Microbiome 5, 4 (2017).
Frese, S. A., Parker, Ok., Calvert, C. C. & Mills, D. A. Diet shapes the intestine microbiome of pigs throughout nursing and weaning. Microbiome 3, 28 (2015).
Fallani, M. et al. Determinants of the human toddler intestinal microbiota after the introduction of first complementary meals in toddler samples from 5 European centres. Microbiol. Read. Engl. 157, 1385–1392 (2011).
Li, Q., Lauber, C. L., Czarnecki-Maulden, G., Pan, Y. & Hannah, S. S. Effects of the dietary protein and carbohydrate ratio on intestine microbiomes in dogs of various physique circumstances. MBio 8, e01703–e01716 (2017).
Alessandri, G. et al. Metagenomic dissection of the canine intestine microbiota: Insights into taxonomic, metabolic and dietary options. Environ. Microbiol. 21, 1331–1343 (2019).
Vital, M., Howe, A. C. & Tiedje, J. M. Revealing the bacterial butyrate synthesis pathways by analyzing (meta)genomic knowledge. Bio 5, e00889*14 (2014).
Lapébie, P., Lombard, V., Drula, E., Terrapon, N. & Henrissat, B. Bacteroidetes use hundreds of enzyme combos to interrupt down glycans. Nat. Commun. 10, 2043 (2019).
Litvak, Y., Byndloss, M. X. & Bäumler, A. J. Colonocyte metabolism shapes the intestine microbiota. Science 362, 1017 (2018).
Sanidad, Ok. Z. & Zeng, M. Y. Neonatal intestine microbiome and immunity. Curr. Opin. Microbiol. 56, 30–37 (2020).
Buddington, R. Ok. Postnatal modifications in bacterial populations within the gastrointestinal tract of dogs. Am. J. Vet. Res. 64, 646–651 (2003).
Chaucheyras-Durand, F., Sacy, A., Karges, Ok. & Apper, E. Gastro-intestinal microbiota in equines and its position in well being and illness: The black field opens. Microorganisms 10, 2517 (2022).
Rinninella, E. et al. What is the wholesome intestine microbiota composition? A altering ecosystem throughout age, setting, eating regimen, and ailments. Microorganisms 7, 14 (2019).
Slifierz, M. J., Friendship, R. M. & Weese, J. S. Longitudinal research of the early-life fecal and nasal microbiotas of the home pig. BMC Microbiol. 15, 184 (2015).
Arboleya, S., Solís, G., Fernández, N., de los Reyes-Gavilán, C. G. & Gueimonde, M. (2012) Facultative to strict anaerobes ratio within the preterm toddler microbiota. Gut Microbes 3, 583–588.
Arboleya, S. et al. Establishment and growth of intestinal microbiota in preterm neonates. FEMS Microbiol. Ecol. 79, 763–772 (2012).
Matamoros, S., Gras-Leguen, C., Le Vacon, F., Potel, G. & de La Cochetiere, M.-F. Development of intestinal microbiota in infants and its affect on well being. Trends Microbiol. 21, 167–173 (2013).
Magne, F. et al. Low species variety and excessive interindividual variability in faeces of preterm infants as revealed by sequences of 16S rRNA genes and PCR-temporal temperature gradient gel electrophoresis profiles. FEMS Microbiol. Ecol. 57, 128–138 (2006).
Minamoto, Y. et al. Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel illness. Gut Microbes 6, 33–47 (2015).
Suchodolski, J. S., Dowd, S. E., Wilke, V., Steiner, J. M. & Jergens, A. E. 16S rRNA gene pyrosequencing reveals bacterial dysbiosis within the duodenum of dogs with idiopathic inflammatory bowel illness. PLoS ONE 7, e39333 (2012).
Berry, A. S. F. et al. Gut microbiota options related to Clostridioides difficile colonization in puppies. PLoS ONE 14, e0215497 (2019).
Münnich, A. & Lübke-Becker, A. Escherichia coli infections in new child puppies—Clinical and epidemiological investigations. Theriogenology 62, 562–575 (2004).
Blake, A. B. et al. Developmental phases in microbiota, bile acids, and clostridial species in wholesome puppies. J. Vet. Intern. Med. 34, 2345–2356 (2020).
García, J. A., Navarro, M. A., Fresneda, Ok. & Uzal, F. A. Clostridium piliforme an infection (Tyzzer illness) in horses: Retrospective research of 25 circumstances and literature evaluate. J. Vet. Diagn. Investig. 34, 421–428 (2022).
Pritt, S., Henderson, Ok. S. & Shek, W. R. Evaluation of accessible diagnostic strategies for Clostridium piliforme in laboratory rabbits (Oryctolagus cuniculus). Lab. Anim. 44, 14–19 (2010).
Headley, S. A., Shirota, Ok., Baba, T., Ikeda, T. & Sukura, A. Diagnostic train: Tyzzer’s illness, distemper, and coccidiosis in a pup. Vet. Pathol. 46, 151–154 (2009).
Young, J. Ok., Baker, D. C. & Burney, D. P. Naturally ocurring Tyzzer’s illness in a puppy. Vet. Pathol. 32, 63–65 (1995).
Cilieborg, M. S., Boye, M., Mølbak, L., Thymann, T. & Sangild, P. T. Preterm start and necrotizing enterocolitis alter intestine colonization in pigs. Pediatr. Res. 69, 10–16 (2011).
Mila, H., Grellet, A., Feugier, A. & Chastant-Maillard, S. Differential affect of start weight and early progress on neonatal mortality in puppies1,2. J. Anim. Sci. 93, 4436–4442 (2015).
Mugnier, A. et al. Low and really low start weight in puppies: Definitions, danger components and survival in a large-scale inhabitants. BMC Vet. Res. 16, 354 (2020).
Pedrogo, D. A. M. et al. Gut microbial carbohydrate metabolism hinders weight reduction in obese adults present process way of life intervention with a volumetric eating regimen. Mayo Clin. Proc. 93, 1104–1110 (2018).
Rampelli, S. et al. Pre-obese youngsters’s dysbiotic intestine microbiome and unhealthy diets might predict the event of weight problems. Commun. Biol. 1, 1–11 (2018).
Apper, E. et al. Relationships between intestine microbiota, metabolome, physique weight, and glucose homeostasis of overweight dogs fed with diets differing in prebiotic and protein content material. Microorganisms 8, 513 (2020).
Mugnier, A. et al. Association between start weight and danger of obese at maturity in Labrador dogs. PLoS ONE 15, e0243820 (2020).
Gethings-Behncke, C. et al. Fusobacterium nucleatum within the colorectum and its affiliation with most cancers danger and survival: A scientific evaluate and meta-analysis. Cancer Epidemiol. Biomark. Prev. 29, 539–548 (2020).
Khan, M. T., van Dijl, J. M. & Harmsen, H. J. M. Antioxidants maintain the possibly probiotic however extremely oxygen-sensitive human intestine bacterium Faecalibacterium prausnitzii alive at ambient air. PLoS ONE 9, e96097 (2014).
Pilla, R. et al. Effects of metronidazole on the fecal microbiome and metabolome in wholesome dogs. J. Vet. Intern. Med. 34, 1853–1866 (2020).
Chaitman, J. et al. Fecal microbial and metabolic profiles in dogs with acute diarrhea receiving both fecal microbiota transplantation or oral metronidazole. Front. Vet. Sci. 7, 192 (2020).
Ferreira-Halder, C. V., de Faria, A. V. S. & Andrade, S. S. Action and performance of Faecalibacterium prausnitzii in well being and illness. Best Pract. Res. Clin. Gastroenterol. 31, 643–648 (2017).
AlShawaqfeh, M. Ok. et al. A dysbiosis index to evaluate microbial modifications in fecal samples of dogs with continual inflammatory enteropathy. FEMS Microbiol. Ecol. 93, 136 (2017).
Beller, L. et al. Successional phases in toddler intestine microbiota maturation. MBio 12, e0185721 (2021).
Tailford, L. E., Crost, E. H., Kavanaugh, D. & Juge, N. Mucin glycan foraging within the human intestine microbiome. Front. Genet. 6, 81 (2015).
Chastant, S. et al. Suckling conduct of puppies in the course of the first 24 hours of life. In Proceedings of the twenty second Congress of European Veterinary Society for Small Animal Reproduction (EVSSAR) vol. 54 Suppl. 2 p. 54 (2019).
Tibbs, T. N., Lopez, L. R. & Arthur, J. C. The affect of the microbiota on immune growth, continual irritation, and most cancers within the context of getting old. Microb. Cell 6, 324–334 (2019).
Fouhse, J. M. et al. Outcomes of a low start weight phenotype on piglet intestine microbial composition and intestinal transcriptomic profile. Can. J. Anim. Sci. 100, 47–58 (2020).
Gaukroger, C. H. et al. Changes in faecal microbiota profiles related to efficiency and birthweight of piglets. Front. Microbiol. 11, 917 (2020).
Vilson, Å. et al. Disentangling components that form the intestine microbiota in German Shepherd dogs. PLoS ONE 13, e0193507 (2018).
Bhang, E., Rao, A. & Robinson, A. A possible age-dependent impact of antibiotics on the intestine microbiome in dogs with inflammatory bowel illness. Undergrad. J. Exp. Microbiol. Immunol. 7, (2021).
Laflamme, D. Development and validation of a physique situation rating system for dogs. Canine Pract. 22, 10–15 (1997).
Veronesi, M. C., Panzani, S., Faustini, M. & Rota, A. An Apgar scoring system for routine evaluation of new child puppy viability and short-term survival prognosis. Theriogenology 72, 401–407 (2009).
Muyzer, G., de Waal, E. C. & Uitterlinden, A. G. Profiling of advanced microbial populations by denaturing gradient gel electrophoresis evaluation of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700 (1993).
Caporaso, J. G. et al. Global patterns of 16S rRNA variety at a depth of hundreds of thousands of sequences per pattern. Proc. Natl. Acad. Sci. USA 108(1), 4516–4522 (2011).
Callahan, B. J. et al. DADA2: High-resolution pattern inference from Illumina amplicon knowledge. Nat. Methods 13, 581–583 (2016).
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome knowledge science utilizing QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).
Katoh, Ok., Misawa, Ok., Kuma, Ok. & Miyata, T. MAFFT: A novel technique for speedy a number of sequence alignment based mostly on quick Fourier rework. Nucleic Acids Res. 30, 3059–3066 (2002).
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–roughly maximum-likelihood timber for giant alignments. PLoS ONE 5, e9490 (2010).
Bokulich, N. A. et al. q2-longitudinal: Longitudinal and paired-sample analyses of microbiome knowledge. Systems 3, e00219-18 (2018).
Shannon, C. E. & Weaver, W. A mathematical concept of communication. Univ. Ill. Press Urbana 27, 379–423 (1949).
McMurdie, P. J. & Holmes, S. phyloseq: An R bundle for reproducible interactive evaluation and graphics of microbiome census knowledge. PLoS ONE 8, e61217 (2013).
Rohart, F., Gautier, B., Singh, A. & Cao, Ok.-A.L. mixOmics: An R bundle for ‘omics characteristic choice and a number of knowledge integration. PLOS Comput. Biol. 13, e1005752 (2017).
Ghasemi, A. & Zahediasl, S. Normality exams for statistical evaluation: A information for non-statisticians. Int. J. Endocrinol. Metab. 10, 486–489 (2012).
van den Boogaart, Ok. G. & Tolosana-Delgado, R. “Compositions”: A unified R bundle to research compositional knowledge. Comput. Geosci. 34, 320–338 (2008).
Akarachantachote, N., Chadcham, S. & Saithanu, Ok. Cutoff threshold of variable significance in projection for variable choice. Int. J. Pure Appl. Math. 94, 307–322 (2014).