Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future
The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing metha...
Ausführliche Beschreibung
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2018 |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
In: Frontiers in Microbiology - Frontiers Media S.A., 2011, 9(2018) |
---|---|
Übergeordnetes Werk: |
volume:9 ; year:2018 |
Links: |
---|
DOI / URN: |
10.3389/fmicb.2018.02161 |
---|
Katalog-ID: |
DOAJ017333083 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ017333083 | ||
003 | DE-627 | ||
005 | 20230310090847.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230226s2018 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.3389/fmicb.2018.02161 |2 doi | |
035 | |a (DE-627)DOAJ017333083 | ||
035 | |a (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
050 | 0 | |a QR1-502 | |
100 | 0 | |a Sharon A. Huws |e verfasserin |4 aut | |
245 | 1 | 0 | |a Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
264 | 1 | |c 2018 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. | ||
650 | 4 | |a rumen | |
650 | 4 | |a microbiome | |
650 | 4 | |a host | |
650 | 4 | |a diet | |
650 | 4 | |a production | |
650 | 4 | |a methane | |
653 | 0 | |a Microbiology | |
700 | 0 | |a Christopher J. Creevey |e verfasserin |4 aut | |
700 | 0 | |a Linda B. Oyama |e verfasserin |4 aut | |
700 | 0 | |a Itzhak Mizrahi |e verfasserin |4 aut | |
700 | 0 | |a Stuart E. Denman |e verfasserin |4 aut | |
700 | 0 | |a Milka Popova |e verfasserin |4 aut | |
700 | 0 | |a Rafael Muñoz-Tamayo |e verfasserin |4 aut | |
700 | 0 | |a Evelyne Forano |e verfasserin |4 aut | |
700 | 0 | |a Sinead M. Waters |e verfasserin |4 aut | |
700 | 0 | |a Matthias Hess |e verfasserin |4 aut | |
700 | 0 | |a Ilma Tapio |e verfasserin |4 aut | |
700 | 0 | |a Hauke Smidt |e verfasserin |4 aut | |
700 | 0 | |a Sophie J. Krizsan |e verfasserin |4 aut | |
700 | 0 | |a David R. Yáñez-Ruiz |e verfasserin |4 aut | |
700 | 0 | |a Alejandro Belanche |e verfasserin |4 aut | |
700 | 0 | |a Leluo Guan |e verfasserin |4 aut | |
700 | 0 | |a Robert J. Gruninger |e verfasserin |4 aut | |
700 | 0 | |a Tim A. McAllister |e verfasserin |4 aut | |
700 | 0 | |a C. Jamie Newbold |e verfasserin |4 aut | |
700 | 0 | |a Rainer Roehe |e verfasserin |4 aut | |
700 | 0 | |a Richard J. Dewhurst |e verfasserin |4 aut | |
700 | 0 | |a Tim J. Snelling |e verfasserin |4 aut | |
700 | 0 | |a Mick Watson |e verfasserin |4 aut | |
700 | 0 | |a Garret Suen |e verfasserin |4 aut | |
700 | 0 | |a Elizabeth H. Hart |e verfasserin |4 aut | |
700 | 0 | |a Alison H. Kingston-Smith |e verfasserin |4 aut | |
700 | 0 | |a Nigel D. Scollan |e verfasserin |4 aut | |
700 | 0 | |a Rodolpho M. do Prado |e verfasserin |4 aut | |
700 | 0 | |a Eduardo J. Pilau |e verfasserin |4 aut | |
700 | 0 | |a Hilario C. Mantovani |e verfasserin |4 aut | |
700 | 0 | |a Graeme T. Attwood |e verfasserin |4 aut | |
700 | 0 | |a Joan E. Edwards |e verfasserin |4 aut | |
700 | 0 | |a Neil R. McEwan |e verfasserin |4 aut | |
700 | 0 | |a Steven Morrisson |e verfasserin |4 aut | |
700 | 0 | |a Olga L. Mayorga |e verfasserin |4 aut | |
700 | 0 | |a Christopher Elliott |e verfasserin |4 aut | |
700 | 0 | |a Diego P. Morgavi |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Frontiers in Microbiology |d Frontiers Media S.A., 2011 |g 9(2018) |w (DE-627)642889384 |w (DE-600)2587354-4 |x 1664302X |7 nnns |
773 | 1 | 8 | |g volume:9 |g year:2018 |
856 | 4 | 0 | |u https://doi.org/10.3389/fmicb.2018.02161 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 |z kostenfrei |
856 | 4 | 0 | |u https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/1664-302X |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 9 |j 2018 |
author_variant |
s a h sah c j c cjc l b o lbo i m im s e d sed m p mp r m t rmt e f ef s m w smw m h mh i t it h s hs s j k sjk d r y r dryr a b ab l g lg r j g rjg t a m tam c j n cjn r r rr r j d rjd t j s tjs m w mw g s gs e h h ehh a h k s ahks n d s nds r m d p rmdp e j p ejp h c m hcm g t a gta j e e jee n r m nrm s m sm o l m olm c e ce d p m dpm |
---|---|
matchkey_str |
article:1664302X:2018----::drsiglbluiatgiutrlhlegshogudrtnighrmnir |
hierarchy_sort_str |
2018 |
callnumber-subject-code |
QR |
publishDate |
2018 |
allfields |
10.3389/fmicb.2018.02161 doi (DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 DE-627 ger DE-627 rakwb eng QR1-502 Sharon A. Huws verfasserin aut Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. rumen microbiome host diet production methane Microbiology Christopher J. Creevey verfasserin aut Linda B. Oyama verfasserin aut Itzhak Mizrahi verfasserin aut Stuart E. Denman verfasserin aut Milka Popova verfasserin aut Rafael Muñoz-Tamayo verfasserin aut Evelyne Forano verfasserin aut Sinead M. Waters verfasserin aut Matthias Hess verfasserin aut Ilma Tapio verfasserin aut Hauke Smidt verfasserin aut Sophie J. Krizsan verfasserin aut David R. Yáñez-Ruiz verfasserin aut Alejandro Belanche verfasserin aut Leluo Guan verfasserin aut Robert J. Gruninger verfasserin aut Tim A. McAllister verfasserin aut C. Jamie Newbold verfasserin aut Rainer Roehe verfasserin aut Richard J. Dewhurst verfasserin aut Tim J. Snelling verfasserin aut Mick Watson verfasserin aut Garret Suen verfasserin aut Elizabeth H. Hart verfasserin aut Alison H. Kingston-Smith verfasserin aut Nigel D. Scollan verfasserin aut Rodolpho M. do Prado verfasserin aut Eduardo J. Pilau verfasserin aut Hilario C. Mantovani verfasserin aut Graeme T. Attwood verfasserin aut Joan E. Edwards verfasserin aut Neil R. McEwan verfasserin aut Steven Morrisson verfasserin aut Olga L. Mayorga verfasserin aut Christopher Elliott verfasserin aut Diego P. Morgavi verfasserin aut In Frontiers in Microbiology Frontiers Media S.A., 2011 9(2018) (DE-627)642889384 (DE-600)2587354-4 1664302X nnns volume:9 year:2018 https://doi.org/10.3389/fmicb.2018.02161 kostenfrei https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 kostenfrei https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full kostenfrei https://doaj.org/toc/1664-302X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2018 |
spelling |
10.3389/fmicb.2018.02161 doi (DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 DE-627 ger DE-627 rakwb eng QR1-502 Sharon A. Huws verfasserin aut Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. rumen microbiome host diet production methane Microbiology Christopher J. Creevey verfasserin aut Linda B. Oyama verfasserin aut Itzhak Mizrahi verfasserin aut Stuart E. Denman verfasserin aut Milka Popova verfasserin aut Rafael Muñoz-Tamayo verfasserin aut Evelyne Forano verfasserin aut Sinead M. Waters verfasserin aut Matthias Hess verfasserin aut Ilma Tapio verfasserin aut Hauke Smidt verfasserin aut Sophie J. Krizsan verfasserin aut David R. Yáñez-Ruiz verfasserin aut Alejandro Belanche verfasserin aut Leluo Guan verfasserin aut Robert J. Gruninger verfasserin aut Tim A. McAllister verfasserin aut C. Jamie Newbold verfasserin aut Rainer Roehe verfasserin aut Richard J. Dewhurst verfasserin aut Tim J. Snelling verfasserin aut Mick Watson verfasserin aut Garret Suen verfasserin aut Elizabeth H. Hart verfasserin aut Alison H. Kingston-Smith verfasserin aut Nigel D. Scollan verfasserin aut Rodolpho M. do Prado verfasserin aut Eduardo J. Pilau verfasserin aut Hilario C. Mantovani verfasserin aut Graeme T. Attwood verfasserin aut Joan E. Edwards verfasserin aut Neil R. McEwan verfasserin aut Steven Morrisson verfasserin aut Olga L. Mayorga verfasserin aut Christopher Elliott verfasserin aut Diego P. Morgavi verfasserin aut In Frontiers in Microbiology Frontiers Media S.A., 2011 9(2018) (DE-627)642889384 (DE-600)2587354-4 1664302X nnns volume:9 year:2018 https://doi.org/10.3389/fmicb.2018.02161 kostenfrei https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 kostenfrei https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full kostenfrei https://doaj.org/toc/1664-302X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2018 |
allfields_unstemmed |
10.3389/fmicb.2018.02161 doi (DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 DE-627 ger DE-627 rakwb eng QR1-502 Sharon A. Huws verfasserin aut Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. rumen microbiome host diet production methane Microbiology Christopher J. Creevey verfasserin aut Linda B. Oyama verfasserin aut Itzhak Mizrahi verfasserin aut Stuart E. Denman verfasserin aut Milka Popova verfasserin aut Rafael Muñoz-Tamayo verfasserin aut Evelyne Forano verfasserin aut Sinead M. Waters verfasserin aut Matthias Hess verfasserin aut Ilma Tapio verfasserin aut Hauke Smidt verfasserin aut Sophie J. Krizsan verfasserin aut David R. Yáñez-Ruiz verfasserin aut Alejandro Belanche verfasserin aut Leluo Guan verfasserin aut Robert J. Gruninger verfasserin aut Tim A. McAllister verfasserin aut C. Jamie Newbold verfasserin aut Rainer Roehe verfasserin aut Richard J. Dewhurst verfasserin aut Tim J. Snelling verfasserin aut Mick Watson verfasserin aut Garret Suen verfasserin aut Elizabeth H. Hart verfasserin aut Alison H. Kingston-Smith verfasserin aut Nigel D. Scollan verfasserin aut Rodolpho M. do Prado verfasserin aut Eduardo J. Pilau verfasserin aut Hilario C. Mantovani verfasserin aut Graeme T. Attwood verfasserin aut Joan E. Edwards verfasserin aut Neil R. McEwan verfasserin aut Steven Morrisson verfasserin aut Olga L. Mayorga verfasserin aut Christopher Elliott verfasserin aut Diego P. Morgavi verfasserin aut In Frontiers in Microbiology Frontiers Media S.A., 2011 9(2018) (DE-627)642889384 (DE-600)2587354-4 1664302X nnns volume:9 year:2018 https://doi.org/10.3389/fmicb.2018.02161 kostenfrei https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 kostenfrei https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full kostenfrei https://doaj.org/toc/1664-302X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2018 |
allfieldsGer |
10.3389/fmicb.2018.02161 doi (DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 DE-627 ger DE-627 rakwb eng QR1-502 Sharon A. Huws verfasserin aut Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. rumen microbiome host diet production methane Microbiology Christopher J. Creevey verfasserin aut Linda B. Oyama verfasserin aut Itzhak Mizrahi verfasserin aut Stuart E. Denman verfasserin aut Milka Popova verfasserin aut Rafael Muñoz-Tamayo verfasserin aut Evelyne Forano verfasserin aut Sinead M. Waters verfasserin aut Matthias Hess verfasserin aut Ilma Tapio verfasserin aut Hauke Smidt verfasserin aut Sophie J. Krizsan verfasserin aut David R. Yáñez-Ruiz verfasserin aut Alejandro Belanche verfasserin aut Leluo Guan verfasserin aut Robert J. Gruninger verfasserin aut Tim A. McAllister verfasserin aut C. Jamie Newbold verfasserin aut Rainer Roehe verfasserin aut Richard J. Dewhurst verfasserin aut Tim J. Snelling verfasserin aut Mick Watson verfasserin aut Garret Suen verfasserin aut Elizabeth H. Hart verfasserin aut Alison H. Kingston-Smith verfasserin aut Nigel D. Scollan verfasserin aut Rodolpho M. do Prado verfasserin aut Eduardo J. Pilau verfasserin aut Hilario C. Mantovani verfasserin aut Graeme T. Attwood verfasserin aut Joan E. Edwards verfasserin aut Neil R. McEwan verfasserin aut Steven Morrisson verfasserin aut Olga L. Mayorga verfasserin aut Christopher Elliott verfasserin aut Diego P. Morgavi verfasserin aut In Frontiers in Microbiology Frontiers Media S.A., 2011 9(2018) (DE-627)642889384 (DE-600)2587354-4 1664302X nnns volume:9 year:2018 https://doi.org/10.3389/fmicb.2018.02161 kostenfrei https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 kostenfrei https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full kostenfrei https://doaj.org/toc/1664-302X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2018 |
allfieldsSound |
10.3389/fmicb.2018.02161 doi (DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 DE-627 ger DE-627 rakwb eng QR1-502 Sharon A. Huws verfasserin aut Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. rumen microbiome host diet production methane Microbiology Christopher J. Creevey verfasserin aut Linda B. Oyama verfasserin aut Itzhak Mizrahi verfasserin aut Stuart E. Denman verfasserin aut Milka Popova verfasserin aut Rafael Muñoz-Tamayo verfasserin aut Evelyne Forano verfasserin aut Sinead M. Waters verfasserin aut Matthias Hess verfasserin aut Ilma Tapio verfasserin aut Hauke Smidt verfasserin aut Sophie J. Krizsan verfasserin aut David R. Yáñez-Ruiz verfasserin aut Alejandro Belanche verfasserin aut Leluo Guan verfasserin aut Robert J. Gruninger verfasserin aut Tim A. McAllister verfasserin aut C. Jamie Newbold verfasserin aut Rainer Roehe verfasserin aut Richard J. Dewhurst verfasserin aut Tim J. Snelling verfasserin aut Mick Watson verfasserin aut Garret Suen verfasserin aut Elizabeth H. Hart verfasserin aut Alison H. Kingston-Smith verfasserin aut Nigel D. Scollan verfasserin aut Rodolpho M. do Prado verfasserin aut Eduardo J. Pilau verfasserin aut Hilario C. Mantovani verfasserin aut Graeme T. Attwood verfasserin aut Joan E. Edwards verfasserin aut Neil R. McEwan verfasserin aut Steven Morrisson verfasserin aut Olga L. Mayorga verfasserin aut Christopher Elliott verfasserin aut Diego P. Morgavi verfasserin aut In Frontiers in Microbiology Frontiers Media S.A., 2011 9(2018) (DE-627)642889384 (DE-600)2587354-4 1664302X nnns volume:9 year:2018 https://doi.org/10.3389/fmicb.2018.02161 kostenfrei https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 kostenfrei https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full kostenfrei https://doaj.org/toc/1664-302X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2018 |
language |
English |
source |
In Frontiers in Microbiology 9(2018) volume:9 year:2018 |
sourceStr |
In Frontiers in Microbiology 9(2018) volume:9 year:2018 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
rumen microbiome host diet production methane Microbiology |
isfreeaccess_bool |
true |
container_title |
Frontiers in Microbiology |
authorswithroles_txt_mv |
Sharon A. Huws @@aut@@ Christopher J. Creevey @@aut@@ Linda B. Oyama @@aut@@ Itzhak Mizrahi @@aut@@ Stuart E. Denman @@aut@@ Milka Popova @@aut@@ Rafael Muñoz-Tamayo @@aut@@ Evelyne Forano @@aut@@ Sinead M. Waters @@aut@@ Matthias Hess @@aut@@ Ilma Tapio @@aut@@ Hauke Smidt @@aut@@ Sophie J. Krizsan @@aut@@ David R. Yáñez-Ruiz @@aut@@ Alejandro Belanche @@aut@@ Leluo Guan @@aut@@ Robert J. Gruninger @@aut@@ Tim A. McAllister @@aut@@ C. Jamie Newbold @@aut@@ Rainer Roehe @@aut@@ Richard J. Dewhurst @@aut@@ Tim J. Snelling @@aut@@ Mick Watson @@aut@@ Garret Suen @@aut@@ Elizabeth H. Hart @@aut@@ Alison H. Kingston-Smith @@aut@@ Nigel D. Scollan @@aut@@ Rodolpho M. do Prado @@aut@@ Eduardo J. Pilau @@aut@@ Hilario C. Mantovani @@aut@@ Graeme T. Attwood @@aut@@ Joan E. Edwards @@aut@@ Neil R. McEwan @@aut@@ Steven Morrisson @@aut@@ Olga L. Mayorga @@aut@@ Christopher Elliott @@aut@@ Diego P. Morgavi @@aut@@ |
publishDateDaySort_date |
2018-01-01T00:00:00Z |
hierarchy_top_id |
642889384 |
id |
DOAJ017333083 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ017333083</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230310090847.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fmicb.2018.02161</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ017333083</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJc3e796147477451e83e0e0fed90a8f00</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QR1-502</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Sharon A. Huws</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">rumen</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">microbiome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">host</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">diet</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">production</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">methane</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Microbiology</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Christopher J. Creevey</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Linda B. Oyama</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Itzhak Mizrahi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Stuart E. Denman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Milka Popova</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rafael Muñoz-Tamayo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Evelyne Forano</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sinead M. Waters</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Matthias Hess</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ilma Tapio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hauke Smidt</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sophie J. Krizsan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">David R. Yáñez-Ruiz</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alejandro Belanche</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Leluo Guan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Robert J. Gruninger</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tim A. McAllister</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">C. Jamie Newbold</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rainer Roehe</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Richard J. Dewhurst</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tim J. Snelling</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mick Watson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Garret Suen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elizabeth H. Hart</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alison H. Kingston-Smith</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Nigel D. Scollan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rodolpho M. do Prado</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Eduardo J. Pilau</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hilario C. Mantovani</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Graeme T. Attwood</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Joan E. Edwards</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Neil R. McEwan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Steven Morrisson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Olga L. Mayorga</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Christopher Elliott</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Diego P. Morgavi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Microbiology</subfield><subfield code="d">Frontiers Media S.A., 2011</subfield><subfield code="g">9(2018)</subfield><subfield code="w">(DE-627)642889384</subfield><subfield code="w">(DE-600)2587354-4</subfield><subfield code="x">1664302X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:9</subfield><subfield code="g">year:2018</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fmicb.2018.02161</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1664-302X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">9</subfield><subfield code="j">2018</subfield></datafield></record></collection>
|
callnumber-first |
Q - Science |
author |
Sharon A. Huws |
spellingShingle |
Sharon A. Huws misc QR1-502 misc rumen misc microbiome misc host misc diet misc production misc methane misc Microbiology Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
authorStr |
Sharon A. Huws |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)642889384 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
callnumber-label |
QR1-502 |
illustrated |
Not Illustrated |
issn |
1664302X |
topic_title |
QR1-502 Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future rumen microbiome host diet production methane |
topic |
misc QR1-502 misc rumen misc microbiome misc host misc diet misc production misc methane misc Microbiology |
topic_unstemmed |
misc QR1-502 misc rumen misc microbiome misc host misc diet misc production misc methane misc Microbiology |
topic_browse |
misc QR1-502 misc rumen misc microbiome misc host misc diet misc production misc methane misc Microbiology |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Frontiers in Microbiology |
hierarchy_parent_id |
642889384 |
hierarchy_top_title |
Frontiers in Microbiology |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)642889384 (DE-600)2587354-4 |
title |
Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
ctrlnum |
(DE-627)DOAJ017333083 (DE-599)DOAJc3e796147477451e83e0e0fed90a8f00 |
title_full |
Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
author_sort |
Sharon A. Huws |
journal |
Frontiers in Microbiology |
journalStr |
Frontiers in Microbiology |
callnumber-first-code |
Q |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2018 |
contenttype_str_mv |
txt |
author_browse |
Sharon A. Huws Christopher J. Creevey Linda B. Oyama Itzhak Mizrahi Stuart E. Denman Milka Popova Rafael Muñoz-Tamayo Evelyne Forano Sinead M. Waters Matthias Hess Ilma Tapio Hauke Smidt Sophie J. Krizsan David R. Yáñez-Ruiz Alejandro Belanche Leluo Guan Robert J. Gruninger Tim A. McAllister C. Jamie Newbold Rainer Roehe Richard J. Dewhurst Tim J. Snelling Mick Watson Garret Suen Elizabeth H. Hart Alison H. Kingston-Smith Nigel D. Scollan Rodolpho M. do Prado Eduardo J. Pilau Hilario C. Mantovani Graeme T. Attwood Joan E. Edwards Neil R. McEwan Steven Morrisson Olga L. Mayorga Christopher Elliott Diego P. Morgavi |
container_volume |
9 |
class |
QR1-502 |
format_se |
Elektronische Aufsätze |
author-letter |
Sharon A. Huws |
doi_str_mv |
10.3389/fmicb.2018.02161 |
author2-role |
verfasserin |
title_sort |
addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future |
callnumber |
QR1-502 |
title_auth |
Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
abstract |
The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. |
abstractGer |
The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. |
abstract_unstemmed |
The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
title_short |
Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future |
url |
https://doi.org/10.3389/fmicb.2018.02161 https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00 https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full https://doaj.org/toc/1664-302X |
remote_bool |
true |
author2 |
Christopher J. Creevey Linda B. Oyama Itzhak Mizrahi Stuart E. Denman Milka Popova Rafael Muñoz-Tamayo Evelyne Forano Sinead M. Waters Matthias Hess Ilma Tapio Hauke Smidt Sophie J. Krizsan David R. Yáñez-Ruiz Alejandro Belanche Leluo Guan Robert J. Gruninger Tim A. McAllister C. Jamie Newbold Rainer Roehe Richard J. Dewhurst Tim J. Snelling Mick Watson Garret Suen Elizabeth H. Hart Alison H. Kingston-Smith Nigel D. Scollan Rodolpho M. do Prado Eduardo J. Pilau Hilario C. Mantovani Graeme T. Attwood Joan E. Edwards Neil R. McEwan Steven Morrisson Olga L. Mayorga Christopher Elliott Diego P. Morgavi |
author2Str |
Christopher J. Creevey Linda B. Oyama Itzhak Mizrahi Stuart E. Denman Milka Popova Rafael Muñoz-Tamayo Evelyne Forano Sinead M. Waters Matthias Hess Ilma Tapio Hauke Smidt Sophie J. Krizsan David R. Yáñez-Ruiz Alejandro Belanche Leluo Guan Robert J. Gruninger Tim A. McAllister C. Jamie Newbold Rainer Roehe Richard J. Dewhurst Tim J. Snelling Mick Watson Garret Suen Elizabeth H. Hart Alison H. Kingston-Smith Nigel D. Scollan Rodolpho M. do Prado Eduardo J. Pilau Hilario C. Mantovani Graeme T. Attwood Joan E. Edwards Neil R. McEwan Steven Morrisson Olga L. Mayorga Christopher Elliott Diego P. Morgavi |
ppnlink |
642889384 |
callnumber-subject |
QR - Microbiology |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.3389/fmicb.2018.02161 |
callnumber-a |
QR1-502 |
up_date |
2024-07-04T01:12:34.948Z |
_version_ |
1803608973587251200 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ017333083</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230310090847.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fmicb.2018.02161</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ017333083</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJc3e796147477451e83e0e0fed90a8f00</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QR1-502</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Sharon A. Huws</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">rumen</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">microbiome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">host</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">diet</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">production</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">methane</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Microbiology</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Christopher J. Creevey</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Linda B. Oyama</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Itzhak Mizrahi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Stuart E. Denman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Milka Popova</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rafael Muñoz-Tamayo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Evelyne Forano</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sinead M. Waters</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Matthias Hess</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ilma Tapio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hauke Smidt</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sophie J. Krizsan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">David R. Yáñez-Ruiz</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alejandro Belanche</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Leluo Guan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Robert J. Gruninger</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tim A. McAllister</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">C. Jamie Newbold</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rainer Roehe</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Richard J. Dewhurst</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Tim J. Snelling</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mick Watson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Garret Suen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elizabeth H. Hart</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alison H. Kingston-Smith</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Nigel D. Scollan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rodolpho M. do Prado</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Eduardo J. Pilau</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hilario C. Mantovani</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Graeme T. Attwood</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Joan E. Edwards</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Neil R. McEwan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Steven Morrisson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Olga L. Mayorga</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Christopher Elliott</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Diego P. Morgavi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Microbiology</subfield><subfield code="d">Frontiers Media S.A., 2011</subfield><subfield code="g">9(2018)</subfield><subfield code="w">(DE-627)642889384</subfield><subfield code="w">(DE-600)2587354-4</subfield><subfield code="x">1664302X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:9</subfield><subfield code="g">year:2018</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fmicb.2018.02161</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/c3e796147477451e83e0e0fed90a8f00</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/article/10.3389/fmicb.2018.02161/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1664-302X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">9</subfield><subfield code="j">2018</subfield></datafield></record></collection>
|
score |
7.399699 |