Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments
Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cai, Lin [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2013 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2013 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Applied microbiology and biotechnology - Springer Berlin Heidelberg, 1984, 97(2013), 21 vom: 23. Jan., Seite 9579-9588 |
|---|---|
| Übergeordnetes Werk: |
volume:97 ; year:2013 ; number:21 ; day:23 ; month:01 ; pages:9579-9588 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00253-012-4678-8 |
|---|
| Katalog-ID: |
OLC2050753942 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2050753942 | ||
| 003 | DE-627 | ||
| 005 | 20230507230345.0 | ||
| 007 | tu | ||
| 008 | 200820s2013 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s00253-012-4678-8 |2 doi | |
| 035 | |a (DE-627)OLC2050753942 | ||
| 035 | |a (DE-He213)s00253-012-4678-8-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 570 |q VZ |
| 084 | |a 12 |2 ssgn | ||
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 100 | 1 | |a Cai, Lin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| 264 | 1 | |c 2013 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer-Verlag Berlin Heidelberg 2013 | ||
| 520 | |a Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. | ||
| 650 | 4 | |a Arsenic | |
| 650 | 4 | |a Arsenic metabolism | |
| 650 | 4 | |a Arsenic metabolism genes | |
| 650 | 4 | |a Metagenome | |
| 650 | 4 | |a Metatranscriptome | |
| 650 | 4 | |a High-throughput sequencing | |
| 700 | 1 | |a Yu, Ke |4 aut | |
| 700 | 1 | |a Yang, Ying |4 aut | |
| 700 | 1 | |a Chen, Bao-wei |4 aut | |
| 700 | 1 | |a Li, Xiang-dong |4 aut | |
| 700 | 1 | |a Zhang, Tong |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Applied microbiology and biotechnology |d Springer Berlin Heidelberg, 1984 |g 97(2013), 21 vom: 23. Jan., Seite 9579-9588 |w (DE-627)129942634 |w (DE-600)392453-1 |w (DE-576)015507750 |x 0175-7598 |7 nnns |
| 773 | 1 | 8 | |g volume:97 |g year:2013 |g number:21 |g day:23 |g month:01 |g pages:9579-9588 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s00253-012-4678-8 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a FID-BIODIV | ||
| 912 | |a SSG-OLC-TEC | ||
| 912 | |a SSG-OLC-CHE | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a SSG-OLC-DE-84 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_130 | ||
| 912 | |a GBV_ILN_267 | ||
| 912 | |a GBV_ILN_2018 | ||
| 912 | |a GBV_ILN_4012 | ||
| 912 | |a GBV_ILN_4082 | ||
| 912 | |a GBV_ILN_4277 | ||
| 912 | |a GBV_ILN_4305 | ||
| 951 | |a AR | ||
| 952 | |d 97 |j 2013 |e 21 |b 23 |c 01 |h 9579-9588 | ||
| author_variant |
l c lc k y ky y y yy b w c bwc x d l xdl t z tz |
|---|---|
| matchkey_str |
article:01757598:2013----::eaeoiepoaineelhglvlomcoilreimtblsgnsncia |
| hierarchy_sort_str |
2013 |
| publishDate |
2013 |
| allfields |
10.1007/s00253-012-4678-8 doi (DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Cai, Lin verfasserin aut Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing Yu, Ke aut Yang, Ying aut Chen, Bao-wei aut Li, Xiang-dong aut Zhang, Tong aut Enthalten in Applied microbiology and biotechnology Springer Berlin Heidelberg, 1984 97(2013), 21 vom: 23. Jan., Seite 9579-9588 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 https://doi.org/10.1007/s00253-012-4678-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 AR 97 2013 21 23 01 9579-9588 |
| spelling |
10.1007/s00253-012-4678-8 doi (DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Cai, Lin verfasserin aut Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing Yu, Ke aut Yang, Ying aut Chen, Bao-wei aut Li, Xiang-dong aut Zhang, Tong aut Enthalten in Applied microbiology and biotechnology Springer Berlin Heidelberg, 1984 97(2013), 21 vom: 23. Jan., Seite 9579-9588 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 https://doi.org/10.1007/s00253-012-4678-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 AR 97 2013 21 23 01 9579-9588 |
| allfields_unstemmed |
10.1007/s00253-012-4678-8 doi (DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Cai, Lin verfasserin aut Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing Yu, Ke aut Yang, Ying aut Chen, Bao-wei aut Li, Xiang-dong aut Zhang, Tong aut Enthalten in Applied microbiology and biotechnology Springer Berlin Heidelberg, 1984 97(2013), 21 vom: 23. Jan., Seite 9579-9588 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 https://doi.org/10.1007/s00253-012-4678-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 AR 97 2013 21 23 01 9579-9588 |
| allfieldsGer |
10.1007/s00253-012-4678-8 doi (DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Cai, Lin verfasserin aut Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing Yu, Ke aut Yang, Ying aut Chen, Bao-wei aut Li, Xiang-dong aut Zhang, Tong aut Enthalten in Applied microbiology and biotechnology Springer Berlin Heidelberg, 1984 97(2013), 21 vom: 23. Jan., Seite 9579-9588 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 https://doi.org/10.1007/s00253-012-4678-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 AR 97 2013 21 23 01 9579-9588 |
| allfieldsSound |
10.1007/s00253-012-4678-8 doi (DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Cai, Lin verfasserin aut Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing Yu, Ke aut Yang, Ying aut Chen, Bao-wei aut Li, Xiang-dong aut Zhang, Tong aut Enthalten in Applied microbiology and biotechnology Springer Berlin Heidelberg, 1984 97(2013), 21 vom: 23. Jan., Seite 9579-9588 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 https://doi.org/10.1007/s00253-012-4678-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 AR 97 2013 21 23 01 9579-9588 |
| language |
English |
| source |
Enthalten in Applied microbiology and biotechnology 97(2013), 21 vom: 23. Jan., Seite 9579-9588 volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 |
| sourceStr |
Enthalten in Applied microbiology and biotechnology 97(2013), 21 vom: 23. Jan., Seite 9579-9588 volume:97 year:2013 number:21 day:23 month:01 pages:9579-9588 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing |
| dewey-raw |
570 |
| isfreeaccess_bool |
false |
| container_title |
Applied microbiology and biotechnology |
| authorswithroles_txt_mv |
Cai, Lin @@aut@@ Yu, Ke @@aut@@ Yang, Ying @@aut@@ Chen, Bao-wei @@aut@@ Li, Xiang-dong @@aut@@ Zhang, Tong @@aut@@ |
| publishDateDaySort_date |
2013-01-23T00:00:00Z |
| hierarchy_top_id |
129942634 |
| dewey-sort |
3570 |
| id |
OLC2050753942 |
| 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">OLC2050753942</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230507230345.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2013 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00253-012-4678-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2050753942</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00253-012-4678-8-p</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="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">12</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cai, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag Berlin Heidelberg 2013</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic metabolism</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic metabolism genes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Metagenome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Metatranscriptome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">High-throughput sequencing</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Ke</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Ying</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Bao-wei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Xiang-dong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Tong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Applied microbiology and biotechnology</subfield><subfield code="d">Springer Berlin Heidelberg, 1984</subfield><subfield code="g">97(2013), 21 vom: 23. Jan., Seite 9579-9588</subfield><subfield code="w">(DE-627)129942634</subfield><subfield code="w">(DE-600)392453-1</subfield><subfield code="w">(DE-576)015507750</subfield><subfield code="x">0175-7598</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:97</subfield><subfield code="g">year:2013</subfield><subfield code="g">number:21</subfield><subfield code="g">day:23</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:9579-9588</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00253-012-4678-8</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</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_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</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_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_130</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_267</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</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_4082</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">97</subfield><subfield code="j">2013</subfield><subfield code="e">21</subfield><subfield code="b">23</subfield><subfield code="c">01</subfield><subfield code="h">9579-9588</subfield></datafield></record></collection>
|
| author |
Cai, Lin |
| spellingShingle |
Cai, Lin ddc 570 ssgn 12 fid BIODIV misc Arsenic misc Arsenic metabolism misc Arsenic metabolism genes misc Metagenome misc Metatranscriptome misc High-throughput sequencing Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| authorStr |
Cai, Lin |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)129942634 |
| format |
Article |
| dewey-ones |
570 - Life sciences; biology |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0175-7598 |
| topic_title |
570 VZ 12 ssgn BIODIV DE-30 fid Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments Arsenic Arsenic metabolism Arsenic metabolism genes Metagenome Metatranscriptome High-throughput sequencing |
| topic |
ddc 570 ssgn 12 fid BIODIV misc Arsenic misc Arsenic metabolism misc Arsenic metabolism genes misc Metagenome misc Metatranscriptome misc High-throughput sequencing |
| topic_unstemmed |
ddc 570 ssgn 12 fid BIODIV misc Arsenic misc Arsenic metabolism misc Arsenic metabolism genes misc Metagenome misc Metatranscriptome misc High-throughput sequencing |
| topic_browse |
ddc 570 ssgn 12 fid BIODIV misc Arsenic misc Arsenic metabolism misc Arsenic metabolism genes misc Metagenome misc Metatranscriptome misc High-throughput sequencing |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Applied microbiology and biotechnology |
| hierarchy_parent_id |
129942634 |
| dewey-tens |
570 - Life sciences; biology |
| hierarchy_top_title |
Applied microbiology and biotechnology |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 |
| title |
Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| ctrlnum |
(DE-627)OLC2050753942 (DE-He213)s00253-012-4678-8-p |
| title_full |
Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| author_sort |
Cai, Lin |
| journal |
Applied microbiology and biotechnology |
| journalStr |
Applied microbiology and biotechnology |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science |
| recordtype |
marc |
| publishDateSort |
2013 |
| contenttype_str_mv |
txt |
| container_start_page |
9579 |
| author_browse |
Cai, Lin Yu, Ke Yang, Ying Chen, Bao-wei Li, Xiang-dong Zhang, Tong |
| container_volume |
97 |
| class |
570 VZ 12 ssgn BIODIV DE-30 fid |
| format_se |
Aufsätze |
| author-letter |
Cai, Lin |
| doi_str_mv |
10.1007/s00253-012-4678-8 |
| dewey-full |
570 |
| title_sort |
metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| title_auth |
Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| abstract |
Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. © Springer-Verlag Berlin Heidelberg 2013 |
| abstractGer |
Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. © Springer-Verlag Berlin Heidelberg 2013 |
| abstract_unstemmed |
Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique. © Springer-Verlag Berlin Heidelberg 2013 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_23 GBV_ILN_70 GBV_ILN_130 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 |
| container_issue |
21 |
| title_short |
Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments |
| url |
https://doi.org/10.1007/s00253-012-4678-8 |
| remote_bool |
false |
| author2 |
Yu, Ke Yang, Ying Chen, Bao-wei Li, Xiang-dong Zhang, Tong |
| author2Str |
Yu, Ke Yang, Ying Chen, Bao-wei Li, Xiang-dong Zhang, Tong |
| ppnlink |
129942634 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s00253-012-4678-8 |
| up_date |
2024-07-04T02:46:46.193Z |
| _version_ |
1803614899353419776 |
| 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">OLC2050753942</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230507230345.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2013 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00253-012-4678-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2050753942</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00253-012-4678-8-p</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="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">12</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cai, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag Berlin Heidelberg 2013</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic metabolism</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Arsenic metabolism genes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Metagenome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Metatranscriptome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">High-throughput sequencing</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Ke</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Ying</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Bao-wei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Xiang-dong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Tong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Applied microbiology and biotechnology</subfield><subfield code="d">Springer Berlin Heidelberg, 1984</subfield><subfield code="g">97(2013), 21 vom: 23. Jan., Seite 9579-9588</subfield><subfield code="w">(DE-627)129942634</subfield><subfield code="w">(DE-600)392453-1</subfield><subfield code="w">(DE-576)015507750</subfield><subfield code="x">0175-7598</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:97</subfield><subfield code="g">year:2013</subfield><subfield code="g">number:21</subfield><subfield code="g">day:23</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:9579-9588</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00253-012-4678-8</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</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_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</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_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_130</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_267</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</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_4082</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">97</subfield><subfield code="j">2013</subfield><subfield code="e">21</subfield><subfield code="b">23</subfield><subfield code="c">01</subfield><subfield code="h">9579-9588</subfield></datafield></record></collection>
|
| score |
7.401099 |