sasava

Microbial metaproteomics: kubva kumuenzaniso kugadzirisa, kuunganidza data kusvika kuongororo yedata

Wu Enhui, Qiao Liang*

Dhipatimendi reKemistry, Fudan University, Shanghai 200433, China

 

 

 

Microorganisms yakabatana zvakanyanya nezvirwere zvevanhu uye hutano. Nzira yekunzwisisa kuumbwa kwenharaunda dzehutachiona uye mabasa avo inyaya hombe inoda kudzidzwa nekuchimbidza. Mumakore achangopfuura, metaproteomics yave yakakosha tekinoroji nzira yekudzidza kuumbwa uye basa rema microorganisms. Nekudaro, nekuda kwekuoma uye kukwirisa heterogeneity yemasampuri enharaunda, sampuli kugadzirisa, misa spectrometry kutora data uye kuongororwa kwedata kwave iwo matambudziko makuru matatu akatarisana nemetaproteomics parizvino. Mukuongorora kwemetaproteomics, zvinowanzodikanwa kukwidziridza pretreatment yemhando dzakasiyana dzemasampuli uye kutora akasiyana hutachiona kupatsanurwa, kupfumisa, kudhirowa uye lysis zvirongwa. Zvakafanana neproteome yemhando imwe chete, maitiro ekutora data akawanda mumetaproteomics anosanganisira data-dependent acquisition (DDA) mode uye data-independent acquisition (DIA) mode. Iyo DIA data yekutora modhi inogona kunyatso kuunganidza iyo peptide ruzivo rwemuenzaniso uye ine yakakura budiriro mukana. Nekudaro, nekuda kwekuoma kwemasamples emetaproteome, kuongororwa kwayo kweDIA data rave dambudziko guru rinotadzisa kuvharika kwakadzama kwemetaproteomics. Panyaya yekuongorora data, danho rakakosha ndeyekuvaka kweprotein sequence database. Kukura uye kukwana kwedhatabhesi hakungove nekukanganisa kukuru pahuwandu hwekuzivikanwa, asiwo kunokanganisa kuongororwa pamhando uye maitiro ekushanda. Parizvino, chiyero chegoridhe chekuvakwa kwemetaproteome dhatabhesi iprotein sequence database yakavakirwa pametagenome. Panguva imwecheteyo, iyo yeruzhinji dhatabhesi yekusefa nzira yakavakirwa pakutsvaga iterative yakaratidzawo kuva yakasimba inoshanda kukosha. Kubva pamaonero emaitiro chaiwo ekuongorora data, peptide-yakatarisana neDIA nzira dzekuongorora dhata dzakatora mhedziso huru. Nekuvandudzwa kwekudzidza kwakadzama uye hungwaru hwekugadzira, inosimudzira zvikuru iko kurongeka, kufukidzira uye nekumhanyisa ongororo yekuongorora macroproteomic data. Panyaya yekuongorora kwakadzika bioinformatics, nhevedzano yezvishandiso zvetsanangudzo yakagadziridzwa mumakore achangopfuura, ayo anogona kuita rondedzero yemhando padanho reprotein, peptide level uye gene level kuwana kuumbwa kwenharaunda dzehutachiona. Kuenzaniswa nedzimwe nzira dze omics, kuongororwa kwekushanda kwenharaunda dzehutachiona chinhu chakasiyana che macroproteomics. Macroproteomics yave chikamu chakakosha chekuongororwa kweakawanda-omics yenharaunda diki, uye ichine hukuru hwebudiriro maererano nekudzika kwekuvhara, kunzwisiswa kwekuona, uye kuzere kwekuongorora data.

 

01Sample pretreatment

Parizvino, tekinoroji yemetaproteomics yakashandiswa zvakanyanya mukutsvagisa kwe microbiome yemunhu, ivhu, chikafu, gungwa, inoshanda sludge uye mamwe minda. Kuenzaniswa nekuongorora kweproteome yemhando imwe chete, sampuli ye pretreatment ye metaproteome yemasampuli akaoma anotarisana nematambudziko mazhinji. Iyo microbial inoumbwa mumasampuli chaiwo yakaoma, iyo ine simba yakawanda yehuwandu yakakura, sero madziro emadziro emhando dzakasiyana dzema microorganisms akasiyana zvakanyanya, uye sampuli dzinowanzova nehuwandu hwakawanda hweanotambira mapuroteni uye kumwe kusvibiswa. Naizvozvo, mukuongororwa kwemetaproteome, zvinowanzodikanwa kukwirisa mhando dzakasiyana dzemasampuli uye kutora kupatsanurwa kwakasiyana kwehutachiona, kupfumisa, kudhirowa uye lysis zvirongwa.

Kutorwa kwemicrobial metaproteomes kubva kumasamples akasiyana kune zvimwe zvakafanana pamwe nemimwe misiyano, asi parizvino pane kushomeka kweiyo yakabatana pre-processing maitiro emhando dzakasiyana dzemetaproteome samples.

 

02Mass spectrometry data kutora

Mukuongorora kwepfuti yeproteome, musanganiswa wepeptide mushure mekutanga kurapwa unotanga kupatsanurwa mukromatographic column, uye wozopinda mumisa spectrometer yekutora data mushure meionization. Zvakafanana nemhando imwe chete yeproteome kuongororwa, iyo mass spectrometry data acquisition modes mukuongorora macroproteome inosanganisira DDA maitiro uye DIA maitiro.

 

Nekuenderera mberi iteration uye kugadziridzwa kwemass spectrometry zviridzwa, mass spectrometry zviridzwa zvine kunzwisiswa kwepamusoro uye kugadzirisa zvinoiswa kune metaproteome, uye kudzika kwekuvhara kwekuongorora metaproteome kunoramba kuchivandudzwa. Kwenguva yakareba, nhevedzano yemhando yepamusoro-resolution mass spectrometry zviridzwa inotungamirwa neOrbitrap yakashandiswa zvakanyanya mumetaproteome.

 

Tafura 1 yezvinyorwa zvepakutanga inoratidza zvimwe zvidzidzo zvinomiririra metaproteomics kubva 2011 kusvika ikozvino maererano nemhando yemuenzaniso, nzira yekuongorora, mass spectrometry chiridzwa, nzira yekuwana, kuongorora software, uye nhamba yezviziviso.

 

03Mass spectrometry data analysis

3.1 DDA data analysis strategy

3.1.1 Database Search

3.1.2de novosequencing strategy

3.2 DIA data analysis strategy

 

04Kuronga kwemhando uye chirevo chekushanda

Kuumbwa kwenharaunda dzehutachiona pamazinga akasiyana etaxonomic ndeimwe yenzvimbo dzakakosha dzekutsvagisa mukutsvaga kwemicrobiome. Mumakore achangopfuura, nhevedzano yezvishandiso zvetsanangudzo zvakagadziridzwa kuti zvitsanangure mhuka padanho reprotein, peptide level, uye gene level kuti vawane kuumbwa kwenharaunda dzehutachiona.

 

Izvo zvakakosha zvekushanda chirevo ndechekufananidza chinangwa cheprotein sequence neiyo inoshanda protein sequence database. Kushandisa gene function dhatabhesi seGO, COG, KEGG, eggNOG, nezvimwewo, ongororo dzakasiyana-siyana dzinoshanda dzinogona kuitwa pamapuroteni anozivikanwa nemacroproteomes. Maturusi ezvinyorwa anosanganisira Blast2GO, DAVID, KOBAS, nezvimwe.

 

05Pfupiso uye Outlook

Microorganisms inoita basa rakakosha muhutano hwevanhu uye chirwere. Mumakore achangopfuura, metaproteomics yave yakakosha tekinoroji nzira yekudzidza basa renharaunda dzehutachiona. Nzira yekuongorora yemetaproteomics yakafanana neye-single-species proteomics, asi nekuda kwekuoma kwechinhu chekutsvakurudza che metaproteomics, mazano chaiwo ekutsvakurudza anofanirwa kutorwa mune imwe neimwe nhanho yekuongorora, kubva kumuenzaniso wekugadzirira, kutora data kusvika kuongororo yedata. Parizvino, nekuda kwekuvandudzwa kwenzira dzekutanga kurapa, kuenderera mberi kwekuvandudza tekinoroji yehukuru hwema spectrometry uye kukurumidza kusimudzira kwebioinformatics, metaproteomics yaita kufambira mberi kukuru mukudzika kwekuzivikanwa uye chiyero chekushandisa.

 

Mukuita kwekutanga kurapwa kwe macroproteome samples, chimiro chemuenzaniso chinofanirwa kutariswa kutanga. Nzira yekuparadzanisa ma microorganisms kubva kumasero ezvakatipoteredza uye mapuroteni ndeimwe yematambudziko makuru anotarisana ne macroproteomes, uye kuenzanisa pakati pekuita kwekuparadzanisa uye kurasikirwa kwehutachiona idambudziko rinokurumidza kugadziriswa. Chechipiri, kubviswa kweprotein yemicroorganisms kunofanirwa kufunga nezvemisiyano inokonzerwa neiyo structural heterogeneity yemabhakitiriya akasiyana. Macroproteome samples mune yekutevera renji inodawo nzira dzekutanga dzekurapa.

 

Panyaya yezviridzwa zvehukuru spectrometry zviridzwa, mainstream mass spectrometry zviridzwa zvakave shanduko kubva kumisa spectrometers zvichibva paOrbitrap mass analyzers seLTQ-Orbitrap uye Q Exactive kune mass spectrometers zvichibva paion mobility yakabatana nguva-ye-ndege mass analyzers senge timsTOF Pro. . Iyo timsTOF yakatevedzana yezviridzwa zvine ion mobility dimension ruzivo ine yakakwirira yekuona chokwadi, yakaderera yekuona muganho, uye yakanaka kudzokorora. Zvishoma nezvishoma zvakava zvishandiso zvakakosha munzvimbo dzakasiyana-siyana dzekutsvagisa dzinoda kucherechedzwa kwemass spectrometry, senge proteome, metaproteome, uye metabolome yemhando imwe chete. Izvo zvakakosha kuti ticherechedze kuti kwenguva yakareba, iyo ine simba renji yezviridzwa spectrometry zviridzwa zvakaganhurira kudzika kweprotein yekuvhara metaproteome research. Mune ramangwana, misa spectrometry zviridzwa zvine yakakura simba renji zvinogona kuvandudza kunzwisiswa uye kurongeka kweprotein identification mumametaproteomes.

 

Pakutorwa kwedata remass spectrometry, kunyangwe nzira yeDIA yekutora data yakagamuchirwa zvakanyanya muproteome yemhando imwe chete, ongororo zhinji dzazvino macroproteome dzichiri kushandisa iyo DDA data acquisition mode. Iyo DIA data acquisition mode inogona kuwana zvizere ruzivo rwechimedu ion yemuenzaniso, uye kana ichienzaniswa neiyo DDA data acquisition mode, ine mukana wekuwana zvizere ruzivo rwepeptide yemuenzaniso macroproteome. Nekudaro, nekuda kwekuoma kwakanyanya kweDIA data, kuongororwa kweDIA macroproteome data kuchiri kutarisana nematambudziko makuru. Kuvandudzwa kwehungwaru hwekugadzira uye kudzidza kwakadzama kunotarisirwa kuvandudza huchokwadi uye kuzara kweDIA data kuongororwa.

 

Mukuongorora kwedata kwemetaproteomics, imwe yematanho akakosha kuvakwa kweprotein sequence database. Kune dzakakurumbira nzvimbo dzekutsvagisa dzakadai semaruva emudumbu, intestinal microbial dhatabhesi senge IGC neHMP inogona kushandiswa, uye yakanaka yekuzivikanwa mhedzisiro yakawanikwa. Kune mamwe akawanda metaproteomics anoongorora, iyo inonyanya kushanda yekuvaka dhatabhesi ichiri kumisa sampuli-chaiyo protein sequence database yakavakirwa pametagenomic kutevedza data. Kune masamples enharaunda yemicrobial ane yakanyanya kuomarara uye yakakura simba renji, zvinodikanwa kuwedzera kudzika kwekutevedzana kuti uwedzere kuzivikanwa kwemhando yakaderera-yakawanda, nekudaro kuvandudza kuvharika kweiyo protein sequence database. Kana kutevedza data kuchishaikwa, nzira yekutsvaga yekudzokorora inogona kushandiswa kukwirisa dhatabhesi yeruzhinji. Nekudaro, kutsvaga kwekudzokorora kunogona kukanganisa FDR hunhu, saka mibairo yekutsvaga inoda kunyatsotariswa. Pamusoro pezvo, kushanda kwechinyakare FDR mhando yekudzora mhando mukuongorora metaproteomics kuchiri kukosha kuongororwa. Panyaya yehurongwa hwekutsvaga, iyo hybrid spectral raibhurari zano inogona kuvandudza kudzika kwekuvhara kweDIA metaproteomics. Mumakore achangopfuura, raibhurari yakafanotaurwa inogadzirwa yakavakirwa pakudzidza kwakadzama yakaratidza kuita kwepamusoro muDIA proteomics. Zvisinei, metaproteome databases inowanzove ine mamiriyoni ezvinyorwa zveprotein, izvo zvinoguma nehuwandu hwemaraibhurari anofanotaurwa, anoshandisa zvakawanda zvekombiyuta, uye zvinoguma munzvimbo huru yekutsvaga. Mukuwedzera, kufanana pakati peprotein sequences mumametaproteomes kunosiyana zvikuru, zvichiita kuti zvive zvakaoma kuve nechokwadi chechokwadi chemuenzaniso we spectral raibhurari yekufanotaura, saka zvakafanotaurwa spectral raibhurari hazvina kushandiswa zvakanyanya mune metaproteomics. Pamusoro pezvo, mapuroteni matsva ekufungidzira uye nzira dzekutsanangura rondedzero dzinoda kugadzirwa kuti dzishande kune metaproteomics ongororo yemapuroteni akatevedzana-akafanana.

 

Muchidimbu, seyakasimukira microbiome yekutsvagisa tekinoroji, metaproteomics tekinoroji yakawana zvakakosha mhedzisiro yekutsvagisa uye zvakare ine yakakura budiriro mukana.


Nguva yekutumira: Aug-30-2024