Molecular Epidemiology and Evolution in an Outbreak of Fulminant Hepatitis B Virus

Molecular Epidemiology and Evolution in an Outbreak of Fulminant Hepatitis B Virus
Molecular Epidemiology and Evolution in an Outbreak of Fulminant Hepatitis B Virus

J OURNAL OF C LINICAL M ICROBIOLOGY,Apr.2006,p.1288–1294Vol.44,No.4 0095-1137/06/$08.00?0doi:10.1128/JCM.44.4.1288–1294.2006

Copyright?2006,American Society for Microbiology.All Rights Reserved.

Molecular Epidemiology and Evolution in an Outbreak of Fulminant

Hepatitis B Virus

Maria Alma Bracho,1Mar?′a Jose′Gosalbes,1Francisco Gonza′lez,2Andre′s Moya,1

and Fernando Gonza′lez-Candelas1*

Institut Cavanilles de Biodiversitat i Biolog?′a Evolutiva and Departament de Gene`tica,Universitat de Vale`ncia,46071Vale`ncia, Spain,1and Direccio′n General de Salud Pu′blica,Conselleria de Sanitat i Consum,Micer Masco′26,46010Vale`ncia,Spain2 Received27July2005/Returned for modi?cation14October2005/Accepted31January2006

In order to establish the transmission pathway for two outbreak patients affected by fulminant hepatitis B

(FHB)following a shared period of hospitalization,we sequenced the complete genomes of the hepatitis B

viruses(HBV)isolated from them as well as from the suspected common source and11additional controls.

Phylogenetic and statistical analyses of these sequences revealed that the two FHB patients were indeed

infected by a common source and that the fatal development of the disease did not appear to be associated with

any mutation previously reported to be related to FHB.These data have also allowed us to estimate the extent

and distribution of genetic variability along the genomes of HBV genotype D samples from the same source

population.As a result of these analyses,we provide an improved statistical method to individualize the

assignment of each suspected patient and the source of an outbreak and information on which genome region

to analyze in the molecular epidemiological assessment of hepatitis B virus transmission cases.

Hepatitis B virus(HBV),the prototype member of the He-padnaviridae family,causes acute and chronic liver disease, chronically infecting more than400million people worldwide, with an estimated risk of death of25%for chronically infected persons(15),thus representing one of the most serious public health problems.HBV is one of the smallest DNA viruses infecting humans,and its genome comprises a3.2-kb linear strand complementary to a shorter(1,700to2,800nucleotides [nt])strand.The two strands are arranged in a circular,par-tially double-stranded molecule.The genome contains four partially overlapping open reading frames(P[polymerase],C [core],S[surface],and X proteins),with no noncoding regions and about50%of its genome involved in two overlapping reading frames.This extremely compact nature of the HBV genome imposes important limits on viral evolution,a situation designated“constrained evolution”(18).

HBV isolates are grouped into eight major genotypes(des-ignated A to H)with different geographic distributions.Geno-type D is the most prevalent in southern European countries, whereas genotype A has a worldwide distribution.Although there is no clear relationship between HBV genotype and clinical course,they seem to affect disease pro?le,with a higher chance of viral clearance and sustained remission for patients infected with genotype A than for those infected with genotype D(15).

Molecular and serological characterizations of HBV have been used to infer chains and sources of infection in several settings,such as nosocomial infections(11,12,23),mother-to-infant transmission(13),or infections derived from close fa-milial contact(5,38).Different strategies have been employed in these analyses,most of them involving the sequencing of a representative portion of the HBV genome.However,there is no consensus on the best choice of region for this kind of analysis.Several authors have used the core region(11,38), others have employed the S region(13),and many have used more than one region(12).The complete genome sequences of nine isolates were used to study a nosocomial infection involving cardiac transplant patients(23).Recently,the same approach has been used to look for speci?c mutations associ-ated with fulminant hepatitis B(FHB)in several donor-recip-ient pairs(4,7).There have been con?icting reports on the association between speci?c mutations in the HBV genome and fulminant hepatitis,especially in the precore(nt1896)and core(nt1762and1764)promoter regions(2,16,22,28,31). Although nosocomial transmissions were soon identi?ed as a risk factor for HBV(17),the frequent report of this type of infection indicates that it still represents a serious and unsolved problem.However,as this is a well-identi?ed risk and preven-tion measures are known and easy to implement,there is also an increase in the number of plaintiffs seeking?nancial com-pensation from infected patients.Hence,establishing the ori-gin of speci?c HBV infections is frequently required,with implications for public health.

In April2002,two fulminant hepatitis B cases associated with a public hospital in Castello′de la Plana(Spain)were detected,suggesting a possible case of nosocomial transmis-sion.Both patients had been hospitalized in the same surgery service during a few days in late December2001,at the same time as a chronic hepatitis B carrier.All three were determined to be affected by HBV genotype D,the most common geno-type in Spain(6).Here we report the molecular epidemiolog-ical study of the outbreak and several population control sam-ples through sequencing of the complete HBV genome along with a detailed analysis of the molecular evolutionary patterns throughout the different regions of this virus.Furthermore, given the fatal outcome of the disease in the two suspect recipients and the chronic status of the putative donor,this

*Corresponding author.Mailing address:Institut Cavanilles de Biodiversitat i Biologia Evolutiva,Universitat de Vale`ncia,Apartado 22085,46071Vale`ncia,Spain.Phone:(34)963543653.Fax:(34)96 3543670.E-mail:fernando.gonzalez@uv.es.

1288 at Penn State Univ on February 12, 2008 https://www.360docs.net/doc/0c12639777.html, Downloaded from

information allowed us to analyze the possibility of establishing associations between speci?c viral mutations and FHB.

MATERIALS AND METHODS

Fulminant hepatitis B outbreak patients.Two FHB cases were declared in the Spanish city of Castello′de la Plana in early spring2002.The?rst case(patient 15)was a63-year-old male who had been intervened of rectum neoplasia on26 December2001at Hospital General de Castello′.He had received no blood transfusion,chemotherapy,or radiotherapy after surgery.The second case(pa-tient16)was a61-year-old male who had gone through emergency surgery at the same hospital on29December2001due to mesenteric ischemia.Prior to surgery, he had received two chemotherapy sessions due to pulmonary neoplasia,and he attended three further sessions afterwards.He also received seven blood trans-fusions in the next month after surgery.During their stay at the hospital,the two patients occupied different rooms on the same?oor and different surgery rooms were used for their interventions.

Epidemiologic investigation.Upon detection of the outbreak,an epidemio-logic investigation of all patients and medical personnel who used or attended the same facilities at the hospital during the stay of the two FHB cases was undertaken.The search revealed that a52-year-old woman who was suffering from a lymphoma and was a chronic HBV carrier had stayed on the same?oor from30December to1January to get a Hickman catheter implanted.She received no transfusions during this stay at the hospital,and her chemotherapy sessions were not coincidental with the stay of the two FHB patients.She was operated on in a different surgery room than the two FHB patients.No cases positive for hepatitis B surface antigen were detected among the medical per-sonnel of this hospital.

Samples.Serum samples were obtained from14patients infected with HBV from the Hospital Universitari La Fe(Vale`ncia,Spain)and Hospital General

(Castello′de la Plana),including the three patients involved in the outbreak (patients07,15,and16).All outbreak patients were positive for hepatitis B surface antigen,hepatitis B e antibody,and hepatitis B core antibody and neg-ative for hepatitis B e antigen,hepatitis C virus,hepatitis delta virus,and human immunode?ciency virus.Except for the two FHB patients associated with the outbreak,all samples were obtained from chronic hepatitis B patients.

DNA genome ampli?cation and sequencing.Viral DNA was puri?ed from sera with a high pure viral nucleic acid kit(Roche Diagnostics GmbH,Mannheim, Germany)by following the protocol as described by the manufacturer.Puri?ed DNA was stored at?80°C until used.Viral DNA was ampli?ed and sequenced essentially as described previously(34),with minor modi?cations of this strategy for complete genome ampli?cation.PCR products were puri?ed using a high pure PCR product puri?cation kit(Roche Diagnostics GmbH,Mannheim,Ger-many).The puri?ed DNA fragments were directly sequenced by the dideoxy method,using a BigDye Terminator v3.0cycle sequencing ready reaction kit,and analyzed with an ABI PRISM3700sequencer(Applied Biosystems,Foster City, CA).Sequence chromatogram?les were analyzed using the Staden package(30). Nucleotides were numbered in accordance with the system of Stuyver et al.(34). Phylogenetic analysis.Based on the full nucleotide sequences,genetic analysis of the14HBV isolates was undertaken.Virus genotypes were established by comparison to existing sequences from public https://www.360docs.net/doc/0c12639777.html,plete genome sequences were aligned using CLUSTAL W(36)and were re?ned further by visual inspection.Phylogenetic trees were constructed using the neighbor-joining algorithm(27)and maximum likelihood with heuristic search as implemented in PAUP?(35).Both analyses were based on the best-?tting model for nucleotide substitution by use of Akaike’s information criterion(1)according to the strategy implemented in Modeltest3.1(24).The tree topology was evaluated by boot-strap analysis with2,000replicates.

Different tree topologies corresponding to alternative hypotheses of the rela-tionships between each outbreak sample and the controls were speci?ed previ-ously(9),and their likelihoods were compared to the one derived without topological constraints by means of a Shimodaira-Hasegawa test(29)as imple-mented in PAUP?(35)after1,000bootstrap pseudorreplicates.

Analysis of polymorphism.Estimates of the number of synonymous(SY)and nonsynonymous(NSY)substitutions among sequences were obtained using the Nei-Gojobori method(19),as implemented in the MEGA program(14).Poly-morphic sites were evaluated using DnaSP version4.0(26)with a100-nt-wide sliding window and1-nt steps.

Nucleotide sequence accession numbers.The sequences of the14new HBV complete genomes have been deposited in the EMBL database with accession numbers AJ627215to AJ627228.

RESULTS

Molecular epidemiology and outbreak analysis.We have obtained the complete genome sequences of14HBV isolates. Ten of these corresponded to genotype D,including those from the outbreak patients;three were assigned to genotype A; and one to genotype B.All genotype D sequences were3,182 nt long,identical in length to the reference strain HPBAYW (EMBL accession no.J02203)(8,33).The three genotype A sequences had different lengths,of3,209,3,212,and3,221nt, with variation from the reference strain HBVADW2(EMBL accession no.X02763,3,221nt long)(33,37),located around positions40to54,in the genome portion coding for P and pre-S proteins.The genotype B sequence had a total length of 3,215nt,identical to the reference sequence for this genotype, HPBADW1(EMBL accession no.D00329)(21).

The general time-reversible model with a proportion of in-variable sites equal to0.4726and a gamma distribution shape parameter equal to0.7439was chosen as the best model of nucleotide substitution for the15complete genome sequences (another genotype B sequence from the database was included in the analysis)by use of Akaike’s information criterion(1,24). Based on this evolutionary model,a phylogenetic tree was constructed by maximum likelihood and neighbor joining from the corresponding pairwise distance matrix.The topology was evaluated by bootstrap,and it is shown in Fig.1.HBV se-quences grouped according to their genotype with high boot-strap support,and most groups within genotypes were also well supported.Sequences derived from the three outbreak isolates grouped in a single cluster with100%bootstrap support,a?rst indication of their very close relatedness.

To further determine whether the HBV sequences from the outbreak patients were related,we tested three alternative tree topologies(Fig.2)for genotype D sequences,each

represent-FIG.1.Phylogenetic tree constructed with the complete genome sequences of14HBV isolates.Phylogenetic robustness as estimated by a bootstrap analysis is shown at each node.The patient number and genotype for each sequence are indicated.The scale bar represents genetic distance(substitutions per nucleotide).

V OL.44,2006MOLECULAR EPIDEMIOLOGY/EVOLUTION IN AN FHB OUTBREAK1289

at Penn State Univ on February 12, 2008 https://www.360docs.net/doc/0c12639777.html,

Downloaded from

ing the possibility that a particular outbreak sequence actually grouped with the control samples rather than with the two other samples presumably from the outbreak (9).Table 1shows a summary of the results obtained with the Shimodaira-Hasegawa test.The three alternative topologies were signi?-cantly worse than the one shown in Fig.1,which supports the grouping of the three outbreak isolates in a cluster of closely related sequences.Hence,the molecular sequence data pro-vided further support to the epidemiological enquiry and con-?rmed that the three patients were involved in a common transmission chain.

Distribution of genetic variability along the HBV genome.Although using a complete genome sequence provides the max-imum possible amount of information at the sequence level,usu-ally it is not necessary to sequence the complete genomes of different isolates,especially for population and epidemiology studies.However,in these cases it is necessary to use a genome region with the adequate amount of sequence divergence for the problem being studied (10).Hence,we obtained the dis-tribution of genetic variability along the complete HBV ge-nome sequences of genotype D isolates (Fig.3).Genetic vari-ation was not uniformly distributed throughout the HBV genome,with differences larger than 10-fold between regions with the highest and lowest levels of variation.Although there was a trend for the most-variable regions to be located in

genome areas coding for only one gene product (e.g.,within the P gene),there were exceptions in both directions.The region coding for the 3?end of the S gene,which also codes for the central portion of the polymerase,presented a variability level similar to that found in the nearby downstream region coding for the polymerase only.In contrast,the genome por-tion ?anked by these two regions,which codes for the poly-merase only,was one of the most conserved stretches in the entire HBV genome,showing variability levels similar to those found in areas coding for only one gene product,such as the core protein or the amino terminal of the polymerase.

The distribution of synonymous and nonsynonymous substi-tutions among outbreak and genotype D sequences along the viral genome is shown in Fig.4.Substitutions were not distrib-uted at random in overlapping and nonoverlapping coding regions for the 10genotype D sequences.Most synonymous substitutions appeared in the nonoverlapping fragments of the polymerase gene (pol ),as expected from the lower restriction for these changes,since they affect only one protein product and do not alter the encoded amino acid.Conversely,the central portion of this gene,which overlaps the S gene,har-bored substantially more nonsynonymous than synonymous substitutions.The core gene is the least overlapping with pol ,and it displayed a markedly different pattern of substitutions.In both sections of the core gene,overlapping and nonover-lapping with pol ,there were more nonsynonymous than syn-onymous substitutions:39NSY and 36SY and 7NSY and 5SY substitutions,respectively.This was also the case for the X gene,again in both overlapping (14NSY and 5SY)and non-overlapping (13NSY and 5SY)regions.Finally,the S gene,which fully overlaps with pol ,presented a different pattern,with fewer nonsynonymous than synonymous substitutions (40NSY and 54SY).

Mutations associated with FHB.We have tested for the presence of mutations associated with FHB in the patients included in this study,because the two patients that prompted our analysis died shortly after nosocomial infection with HBV.Table 2presents a presence/absence analysis of mutations po-tentially associated with FHB in the sequences included in this study.The analysis shows that the majority of HBV isolates (from both the outbreak and the nonoutbreak patients)

har-

FIG.2.Phylogenies corresponding to testing whether each sequence related to the outbreak is signi?cantly related to the other sequences in this group or to the general population.The patient number and genotype for each sequence are indicated.(a)Sequence from the suspected source,patient 07.(b)Sequence from patient 15.(c)Sequence from patient 16.

TABLE 1.Tests for the alternative hypotheses of each isolate from

the outbreak not belonging to it a

Isolate excluded

Ln b

?c

P

None 7,167.342Best 077,290.979123.636?0.001157,287.886120.544?0.00116

7,290.979123.636

?0.001

a

A one-tailed Shimodaira-Hasegawa test with RELL (1,000replicates)was performed on the topology represented in Fig.1for genotype D sequences and the three alternative topologies (Fig.2),where each outbreak isolate sequence was presumed to group with control samples and not with the two other outbreak isolates.b

Ln,log likelihood.c

??Ln(H1)?Ln(H0),where H0is the topology shown in Fig.1for genotype D sequences,and H1is an alternate topology considering each out-break-related isolate as grouping with control samples.

1290BRACHO ET AL.J.C LIN .M ICROBIOL .

at Penn State Univ on February 12, 2008

https://www.360docs.net/doc/0c12639777.html, Downloaded from

bored one or more mutations presumably linked to FHB.Nev-ertheless,only the two outbreak patients suffered a rapid,fatal development of the disease despite the fact that viruses iso-lated from these two persons had potential FHB mutations identical to those of the virus from the infection source,a chronically infected patient who did not progress to FHB.Most polymorphic sites appearing in the outbreak-related sequences were located in the pol gene (10of 11).Of these,

six

FIG.3.Nucleotide diversity along the HBV genome.The number of polymorphic sites in 100-nt-wide windows among eight complete genotype D genomes sequenced in this study is represented (only one genome sequence from the outbreak was included in this

analysis).

FIG.4.Locations of SY (?)and NSY (?)substitutions in the complete genomes for outbreak (3sequences)and genotype D (10sequences)samples,considering the different overlapping and nonoverlapping gene regions.?,no substitutions were found in the 25nt overlapping core and X genes.These nucleotides have been considered a nonoverlapping part of the core gene.Genome/gene regions are abbreviated as follows.NOC,nonoverlapping core gene;COP,core gene overlapping pol ;POC,pol overlapping core gene;NOP1,nonoverlapping pol ,part 1;POPS,pol overlapping pre-S;PSOP,pre-S overlapping pol ;POS,pol overlapping S,SOP,S overlapping pol ;NOP2,nonoverlapping pol ,part 2;XOP,X overlapping pol ;POX,pol overlapping X;NOX,nonoverlapping X.

V OL .44,2006MOLECULAR EPIDEMIOLOGY/EVOLUTION IN AN FHB OUTBREAK 1291

at Penn State Univ on February 12, 2008

https://www.360docs.net/doc/0c12639777.html, Downloaded from

were nonsynonymous (four overlapping to the S gene and two in the nonoverlapping regions of pol )and four were synony-mous (two in the nonoverlapping regions and one each over-lapping the S and X genes).A summary of some relevant features of these mutations is presented in Table 3.None has been postulated to be associated with FHB,and since none was present in both infected patients and absent in the source it is not possible to invoke any of these mutations as the only cause of the fatal development of the disease in those two persons.

DISCUSSION

Our analyses have revealed substantial genetic variation in the genome sequences of HBV genotype D isolates from the same population and with different degrees of relatedness,from the very closely related isolates recently derived from a common source to the more distant,epidemiologically unre-lated isolates.This has allowed us to establish a clear link between the two outbreak case patients and the putative in-fection source,reinforcing the epidemiological analysis which,without molecular evidence,also gave a strong indication about this transmission case.The complete genome sequences derived from the source and the two infected patients present a small number of differences (eight and nine differences for patients 15and 16,respectively,from a total of 3,218nt),many of which correspond to polymorphic sites in the source that are resolved in the recipients (?ve cases).Similar or even higher numbers of differences (ranging from 0to 43)have been found by full-genome comparisons between HBV isolates from source and recipient pairs in several analyses (4,7,25,32).Our statistical analyses provide strong,additional support for a link between the three full genome sequences considered in the outbreak and additional full genome sequences obtained from HBV-infected individuals from the same population.The ep-idemiological and molecular phylogenetic analyses have led us to conclude that there was a common origin for HBV in the two outbreak patients and that this common source was patient 07,with whom both had been in contact in a public hospital during two days at the end of 2001.

Our study has revealed that genetic variation is not evenly distributed along the HBV genome (Fig.3).Despite the pres-ence of extensive overlapping of coding regions,we found high levels of genetic variation within genotype D sequences ob-

TABLE 2.Mutations proposed to be associated with FHB in the samples analyzed in this study

Patient a Presence/absence b of mutation by region

Enhancer I/X promoter NRE c

Enhancer II/core promoter Precore C/G1249T d

T1250C

A/G1633d

A/G1634d

C1653T

A1752C

T1753C/A/G d

C1754T

A1762T

G1764A

G1896A

07???????????15???????????16???????????20???????????34???????????28???????????25???????????52???????????53???????????39???????????08???????????95???????????77???????????49

???????????

a

Patients 15and 16correspond to the two outbreak patients affected by FHB,and patient 07was their source of infection.The remaining patients in the study were chronic HBV carriers.b

?,presence;?,absence.c

NRE,negative regulator element.d

Nucleotide depends on genotype.

TABLE 3.Analysis of variant sites among the three outbreak-related sequences

Source or location of sequence

Polymorphism a at nt:

289

765

814

1221

1356

1500

1679

2547

2738

3064

3069

Patients 07Y R W R C T A A C G R 15T A A G C C A A Y A A 16C G T A T T C G C G G Genes pol NSY SY

NSY NSY

SY

SY

NSY

SY

NSY NSY Other

SY (S)

NSY (S)

NSY (S)

NSY (X)

SY (X)

NSY (S)

NSY (S)

a

Standard ambiguity codes for nucleotide polymorphism are used.Most sites are located in the pol gene;for those that are not,the relevant gene is reported in parentheses.The nature of the polymorphism is indicated (SY or NSY).

1292BRACHO ET AL.

J.C LIN .M ICROBIOL .

at Penn State Univ on February 12, 2008

https://www.360docs.net/doc/0c12639777.html, Downloaded from

tained from the same population,which provides ample op-portunities for the application of molecular sequence analysis to epidemiological analysis of HBV.Similar patterns of hetero-geneity in genetic variation along the viral genome have been documented previously(3,7,20).In general,the genome re-gion of choice for outbreak analyses depends on the problem in question and its associated time frame,because an adequate level of variation for discriminating among the different alter-natives under consideration must be provided(10).From the data presented here,it is recommended to analyze the most rapidly evolving HBV genomic regions,such as the nonover-lapping stretches in the core and pol genes,for the study of outbreaks or transmission chains or for studies involving se-quences recently derived from a common ancestor.This does not necessarily contradict the“constrained evolution”model for HBV(18),since different evolutionary forces act at differ-ent time scales.Among very closely related isolates,drift and hitchhiking selection,for instance,may contribute to tempo-rary polymorphism in positions that will most likely be lost from the population and will not contribute to differentiation among more distantly related isolates.

Transient polymorphisms,such as those detected in the source but resolved in the outbreak patients,may also explain why some mutations have been associated with fulminant hep-atitis B even though they appear only in some fatally affected patients.We present evidence of such a lack of association in the three patients involved in the analyzed outbreak.However, other reasons may also explain the recurrent presence of this kind of mutation associated with FHB.For instance,it may be that two or more mutations in different positions of the HBV genome are required to produce the fatal effects or that these depend not only on the virus itself but also on other host factors.

Another remarkable feature is the high frequency of non-synonymous mutations among the variants detected.Half of the six mutations appearing in regions where two genes overlap were nonsynonymous for both genes.However,it is possible that they have negative effects on viral?tness and will eventu-ally be removed from the population by purifying selection. Nevertheless,their low frequency prevented their identi?ca-tion as strongly negatively selected codons.Evidently,more studies are needed to completely understand the reasons why such different clinical outcomes should characterize patients affected by very similar viruses.

ACKNOWLEDGMENTS

We thank Eddie Holmes,Mario A.Fare′s,and F.Xavier Lo′pez-Labrador for comments and suggestions to improve the manuscript. This work was supported by Conselleria de Sanidad,Generalitat Valenciana,and project Grupos03/204from Agencia Valenciana de Ciencia y Tecnolog?′a.

REFERENCES

1.Akaike,H.1974.A new look at the statistical model identi?cation.IEEE

(Inst.Electr.Electron.Eng.)Trans.Automatic Control19:716–723.

2.Baumert,T.F.,S.A.Rogers,K.Hasegawa,and T.J.Liang.1996.Two core

promotor mutations identi?ed in a hepatitis B virus strain associated with fulminant hepatitis result in enhanced viral replication.J.Clin.Investig.

98:2268–2276.

3.Bollyky,P.L.,and E.C.Holmes.1999.Reconstructing the complex evolu-

tionary history of hepatitis B virus.J.Mol.Evol.49:130–141.

4.Chen,Y.,K.Michitaka,H.Matsubara,K.Yamamoto,N.Horiike,and M.

https://www.360docs.net/doc/0c12639777.html,plete genome sequence of hepatitis B virus(HBV)from a

patient with fulminant hepatitis without precore and core promoter muta-tions:comparison with HBV from a patient with acute hepatitis infected from the same infectious source.J.Hepatol.38:84–90.

5.Dumpis,U.,E.C.Holmes,M.Mendy,A.Hill,M.Thursz,A.Hall,H.

Whittle,and P.Karayiannis.2001.Transmission of hepatitis B virus infec-tion in Gambian families revealed by phylogenetic analysis.J.Hepatol.

35:99–104.

6.Echevarria,J.M.,A.Avello′n,and L.O.Magnius.2005.Molecular epide-

miology of hepatitis B virus in Spain:identi?cation of viral genotypes and prediction of antigenic subtypes by limited sequencing.J.Med.Virol.76: 176–184.

7.Friedt,M.,P.Gerner,P.Wintermeyer,and https://www.360docs.net/doc/0c12639777.html,plete hep-

atitis B virus genome analysis in HBsAg positive mothers and their infants with fulminant hepatitis B.BMC Gastroenterol.4:11.

8.Galibert,F.,E.Mandart,F.Fitoussi,P.Tiollais,and P.Charnay.1979.

Nucleotide sequence of the hepatitis B virus genome(subtype ayw)cloned in

E.coli.Nature281:646–650.

9.Gonza′lez-Candelas,F.,M.A.Bracho,and A.Moya.2003.Molecular epide-

miology and forensic genetics:application to a hepatitis C virus transmission event at a hemodialysis unit.J.Infect.Dis.187:352–358.

10.Gonza′lez-Candelas,F.,and A.Moya.2005.Time and rate of evolution are

the key to establish transmission cases.AIDS19:1552–1553.

11.Harpaz,R.,L.Von Seidlein,F.M.Averhoff,M.P.Tormey,S.D.Sinha,K.

Kotsopulou,https://www.360docs.net/doc/0c12639777.html,mbert,B.H.Robertson,J.D.Cherry,and C.N.

Shapiro.1996.Transmission of hepatitis B virus to multiple patients from a surgeon without evidence of inadequate infection control.N.Engl.J.Med.

334:549–554.

12.Kidd-Ljunggren,K.,E.Broman,H.Ekvall,and O.Gustavsson.1999.Nos-

ocomial transmission of hepatitis B virus infection through multiple-dose vials.J.Hosp.Infect.43:57–62.

13.Komatsu,H.,A.Inui,Y.Morinishi,T.Sogo,and T.Fujisawa.2001.Se-

quence analysis of hepatitis B virus genomes from an infant with acute severe hepatitis and a hepatitis B e antigen-positive carrier mother.J.Med.Virol.

65:457–462.

14.Kumar,S.,K.Tamura,I.B.Jakobsen,and M.Nei.2000.MEGA:molecular

evolutionary genetics analysis,version2.0b3.[Online.]http://www.megasoftware .net.

https://www.360docs.net/doc/0c12639777.html,i,C.L.,V.Ratziu,M.F.Yuen,and T.Poynard.2003.Viral hepatitis B.

Lancet362:2089–2094.

16.Liang,T.J.,K.Hasegawa,N.Rimon,J.R.Wands,and E.Ben Porath.1991.

A hepatitis

B virus mutant associated with an epidemic of fulminant hepa-

titis.N.Engl.J.Med.324:1705–1709.

17.Lo¨fgren,B.,E.Nordenfelt,T.Lindholm,and B.Linderg?rd.1982.A ten-

year follow-up of a hepatitis B epidemic in a dialysis unit.Scand.J.Infect.

Dis.14:165–169.

18.Mizokami,M.,E.Orito,K.Ohba,K.Ikeo,https://www.360docs.net/doc/0c12639777.html,u,and T.Gojobori.1997.

Constrained evolution with respect to gene overlap of hepatitis B virus.J.

Mol.Evol.44:83–90.

19.Nei,M.,and T.Gojobori.1986.Simple methods for estimating the numbers

of synonymous and nonsynonymous nucleotide substitutions.Mol.Biol.

Evol.3:418–423.

20.Norder,H.,A.M.Courouce,and https://www.360docs.net/doc/0c12639777.html,plete genomes,

phylogenetic relatedness,and structural proteins of six strains of the hepatitis

B virus,four of which represent two new genotypes.Virology198:489–503.

21.Okamoto,H.,M.Imai,M.Shimozaki,Y.Hoshi,H.Iizuka,T.Gotanda,F.

Tsuda,Y.Miyakawa,and M.Mayumi.1986.Nucleotide sequence of a cloned hepatitis B virus genome,subtype ayr:comparison with genomes of the other three subtypes.J.Gen.Virol.67:2305–2314.

22.Omata,M.,T.Ehata,O.Yokosuka,K.Hosoda,and M.Ohto.1991.Muta-

tions in the precore region of hepatitis B virus DNA in patients with fulmi-nant and severe hepatitis.N.Engl.J.Med.324:1699–1704.

23.Petzold,D.R.,B.Tautz,F.Wolf,and J.Drescher.1999.Infection chains and

evolution rates of hepatitis B virus in cardiac transplant recipients infected nosocomially.J.Med.Virol.58:1–10.

24.Posada,D.,and K.A.Crandall.2001.Selecting the best-?t model of nucle-

otide substitution.Syst.Biol.50:580–601.

25.Rokuhara,A.,E.Tanaka,S.Yagi,M.Mizokami,Y.Hashikura,S.Kawasaki,

and K.Kiyosawa.2000.De novo infection of hepatitis B virus in patients with orthotopic liver transplantation:analysis by determining complete se-quence of the genome.J.Med.Virol.62:471–478.

26.Rozas,J.,J.C.Sanchez-DelBarrio,X.Messeguer,and R.Rozas.2003.

DnaSP,DNA polymorphism analyses by the coalescent and other methods.

Bioinformatics19:2496–2497.

27.Saitou,N.,and M.Nei.1987.The neighbor-joining method:a new method

for reconstructing phylogenetic trees.Mol.Biol.Evol.4:406–425.

28.Sato,S.,K.Suzuki,Y.Akahane,K.Akamatsu,K.Akiyama,K.Yunomura,

F.Tsuda,T.Tanaka,H.Okamoto,Y.Miyakawa,and M.Mayumi.1995.

Hepatitis B virus strains with mutations in the core promoter in patients with fulminant hepatitis.Ann.Intern.Med.122:241–248.

29.Shimodaira,H.,and M.Hasegawa.1999.Multiple comparisons of log-

likelihoods with applications to phylogenetic inference.Mol.Biol.Evol.

16:1114–1116.

V OL.44,2006MOLECULAR EPIDEMIOLOGY/EVOLUTION IN AN FHB OUTBREAK1293

at Penn State Univ on February 12, 2008 https://www.360docs.net/doc/0c12639777.html,

Downloaded from

30.Staden,R.,K.Beal,and J.Bon?eld.1999.The Staden package,1998,

p.115–130.In S.Misener and S.Krawetz(ed.),Computer methods in molecular biology.Humana Press,Inc.,Totowa,N.J.

31.Sterneck,M.,S.Gunther,T.Santantonio,L.Fischer,C.E.Broelsch,H.

Greten,and H.Will.1996.Hepatitis B virus genomes of patients with fulminant hepatitis do not share a speci?c mutation.Hepatology24:300–306.

32.Sterneck,M.,T.Kalinina,S.Otto,S.Gunther,L.Fischer,M.Burdelski,H.

Greten,C.E.Broelsch,and H.Will.1998.Neonatal fulminant hepatitis B: structural and functional analysis of complete hepatitis B virus genomes from mother and infant.J.Infect.Dis.177:1378–1381.

33.Stuyver,L.J.,S.A.Locarnini,A.Lok,D.D.Richman,W.F.Carman,J.L.

Dienstag,and R.F.Schinazi.2001.Nomenclature for antiviral-resistant human hepatitis B virus mutations in the polymerase region.Hepatology 33:751–757.

34.Stuyver,L.,S.De Gendt,C.Van Geyt,F.Zoulim,M.Fried,R.F.Schinazi,

and R.Rossau.2000.A new genotype of hepatitis B virus:complete genome and phylogenetic relatedness.J.Gen.Virol.81:67–74.

35.Swofford,D.L.2002.PAUP?:phylogenetic analysis using parsimony(?and

other methods),version4.0beta.Sinauer Associates,Sunderland,Mass. 36.Thompson,J.D.,D.G.Higgins,and T.J.Gibson.1994.CLUSTAL W:

improving the sensitivity of progressive multiple sequence alignment through sequence weighting,positions-speci?c gap penalties and weight matrix choice.Nucleic Acids Res.22:4673–4680.

37.Valenzuela,P.,M.Quiroga,J.Zaldivar,P.Gray,and W.J.Rutter.1980.The

nucleotide sequence of the hepatitis B viral genome and the identi?cation of the major viral genes.Academic Press,New York,N.Y.

38.Zampino,R.,S.Lobello,M.Chiaramonte,C.Venturi-Pasini,U.Dumpis,M.

Thursz,and P.Karayiannis.2002.Intra-familial transmission of hepatitis B virus in Italy:phylogenetic sequence analysis and amino-acid variation of the core gene.J.Hepatol.36:248–253.

1294BRACHO ET AL.J.C LIN.M ICROBIOL.

at Penn State Univ on February 12, 2008 https://www.360docs.net/doc/0c12639777.html,

Downloaded from

细胞线粒体毒性的检测(Molecular Devices)

如何借助于具有SpectraMax MinMax300 细胞成像系统的SpectraMax i3多功能微孔板检测平台进行细胞线粒体毒性的检测 简介 优势 Application Highlight 评价待选新药对细胞线粒体产生的毒性作用一直被认为是药物筛选过程中的关键步骤,目前可轻松通过不同颜色的荧光染料来标记细胞线粒体后来检测其活性的变化,整个检测过程中通常也需要结合细胞核复染色法,例如使用DAPI染料,这样就可以在图像中轻松识别出所有细胞。可以利用成像系统的一个荧光通道识别被染核的细胞,而细胞线粒体活性检测可以通过特定的线粒体染料标记后,来分析第二个荧光通道中每个标记后细胞的荧光信号强度值。然而,细胞核复染色过程会增加一系列额外的操作步骤,使得实验过程变得繁琐、拖延检测时间。来自于Molecule Devices公司的StainFree ?技术(无标记分析技术)可以解放研究人员,使其无需借助于繁琐的细胞核复染色法来识别细胞,可以直接利用SpectraMax ? MiniMax ? 300 细胞成像系统的透射光通道来直接识别出单个细胞。此篇应用文献重点介绍如何利用SpectraMax ? i3多功能微孔板检测平台的细胞成像功能来检测细胞线粒体毒性,缬氨霉素,一种离子型抗生素,可对PC12细胞线粒体功能造成损伤,使用MitoTracker Deep Red FM来标记线粒体后对整个过程进行检测,然后分别使用StainFree方法和细胞核荧光染料标记法对细胞计数,SoftMax Pro软件分析比较两组结果。SpectraMax MiniMax 300细胞成像系统和SoftMax Pro软件组合后,可以帮助研究人员获取图像信息和进行数据分析,准确、快速的给出潜在化合物对细胞线粒体毒性的浓度效应学曲线。 基于细胞检测试验方法的设置 使用含有2.5%胎牛血清、15%的马血清和1%青霉素/链霉素的F-12K培养基来培养PC12(大鼠肾上腺嗜铬瘤细胞)细胞,在黑色底通的96孔板中每孔加入100ul配好的培养基,细胞的密度为10,000/孔,培养过夜。隔天,细胞孔内加入缬氨霉素,其浓度范围是1μM至1nM并按12浓度梯度关系进行稀释,然后将处理后的微孔板放入37度二氧化碳培养箱中培养24小时。完成孵育处理后,将混有化合物的培养基去除,随后加入含有100nM 的MitoTracker Deep Red FM(MTDR)染料的新鲜培养基。此试剂可以标记活细胞中的线粒体,可以利用MinMax 细胞成像系统的远红外荧光通道检测其在远红外波段下的荧光强度值。 细胞孵育30分钟后,去除混有染料的培养基,使用4%多聚甲醛固定细胞,固定后的细胞核使用EarlyTox Dead Green 染料来标记(Molecular Devices cat. #R8216)。虽然固定后是无需使用StainFree方法来分析细胞数目、形态的,但是此目的是比较这次实验中所有细胞在不同通道下获得数据的一致性。利用MinMax 细胞成像系统的透射光通道对细胞进行成像,获取细胞数目和分析其形态变化,利用其红色荧光通道检测其线粒体活性。同样利用系统的绿色荧光通道对染核细胞进行计数分析后与使用透射光通道下StainFree方法计数的细胞进行比较。 使用SoftMax Pro软件,设置两种不同的成像分析方法,第一种分析,单个细胞的识别是通过StainFree方法,可在透射光通道下识别单个细胞而无需利用细胞核荧光染料分子进行标记。为识别每个细胞,在软件中将测量的线粒体的红色荧光信号以一定形式参数输出。 ???StainFree技术无需利用细胞核复染方法就可以对细胞进行成像分析 利用SoftMax Pro软件所具有的细胞成像分析功能,可以检测出基于每一个细胞线粒体荧光信号强度值可更快的获得细胞线粒体毒性检测结果

The neutral theory of molecular evolution分子进化的中性理论

The neutral theory of molecular evolution Introduction I didn’t make a big deal of it in what we just went over,but in deriving the Jukes-Cantor equation I used the phrase“substitution rate”instead of the phrase“mutation rate.”As a preface to what is about to follow,let me explain the di?erence. ?Mutation rate refers to the rate at which changes are incorporated into a nucleotide sequence during the process of replication,i.e.,the probability that an allele di?ers from the copy of that in its parent from which it was derived.Mutation rate refers to the rate at which mutations arise. ?An allele substitution occurs when a newly arisen allele is incorporated into a popula-tion,e.g.,when a newly arisen allele becomes?xed in a population.Substitution rate refers to the rate at which allele substitutions occur. Mutation rates and substitution rates are obviously related related—substitutions can’t happen unless mutations occur,after all—,but it’s important to remember that they refer to di?erent processes. Early empirical observations By the early1960s amino acid sequences of hemoglobins and cytochrome c for many mam-mals had been determined.When the sequences were compared,investigators began to notice that the number of amino acid di?erences between di?erent pairs of mammals seemed to be roughly proportional to the time since they had diverged from one another,as inferred from the fossil record.Zuckerkandl and Pauling[8]proposed the molecular clock hypothesis to explain these results.Speci?cally,they proposed that there was a constant rate of amino acid substitution over time.Sarich and Wilson[6,7]used the molecular clock hypothesis to propose that humans and apes diverged approximately5million years ago.While that c 2001-2012Kent E.Holsinger

检测细胞活性或毒性(Molecular Devices)

Application Highlight 在SpectraMax MiniMax 300细胞成像系统上应用 EarlyTox细胞完整性试剂 盒检测细胞活性或毒性 图1. EarlyTox细胞完整性试剂盒检测原理 Live Red Dye Dead Green Dye Live Cell Dead Cell EarlyTox ?细胞完整性试剂盒由一系列易于识别活细胞和死细胞的优化试剂组成。可用于检测不同处理对细胞活性的影响,也可评估不同机制产生的细胞毒性,包括凋亡和坏死。该试剂盒设计工作于多种细胞类型,贴壁和悬浮均可。简单的操作流程和优异的试剂表现使其能应用到高通量扫描上。试剂盒中使用了两种结合DNA的荧光染料,一种为细胞膜可穿透的活细胞红色染料,一种为细胞膜不可穿透的死细胞绿色染料。红色染料可进入所有细胞的细胞核,细胞膜是否完整对其无影响,并可被激发产生亮红色荧光信号。绿色染料只能进入死细胞并产生亮绿色荧光,此类细胞的细胞膜已不完整(图1)。因此,活细胞和死细胞能通过成像系统拍摄到的荧光信号被轻易区分和识别到。 SpectraMax ? MiniMax ? 300细胞成像系统和SoftMax ? Pro软件为EarlyTox细胞完整性试剂盒的应用提供了成像和数据分析的整套硬件软件工具。使用仪器的双通道荧光成像功能以及软件的单细胞分析功能,可在5分钟内分析一块96孔板细胞活性。 方法 HeLa细胞以5000个/孔的密度接种到黑壁底透384孔板,培养24小时使其贴壁并生长,然后孔中加入具细胞毒性的药物。药物处理24小时候,按照试剂盒说明书加入染料标记后检测细胞活性。操作方法应尽量均一,以减少移除培养基、冲洗步骤造成的细胞损失和结果不准确性。可选的遮蔽试剂能用于减少培养基或待测药物产生的背景值。 特点 ? ? ? 信号强,缩短曝光时间,成像速度更快 适用于各种细胞类型,应用广泛拍照和分析一体完成,流程简化 通过试剂盒中两种不同特性的染料区分出活细胞和死细胞。红色染料进入所有细胞并将其细胞核标记为红色,另外绿色染料能进入具有不完整细胞膜的细胞中,并将其细胞核标记为绿色。只带红色荧光的细胞被成像和识别为活细胞,同时那些既发绿光又发红光的细胞被识别为死细胞。

分子原子原胞晶体显示软件Visual Molecular Dynamics 使用说明

简介: 这个教程为新用户介绍了VMD的用法。老用户也可以用本教程进一步熟悉程序的应用,以更好地利用VMD。本教程是针对VMD 1.8.3设计的,需要约3个小时来完成。 本教程新增的内容可用三个独立的单元讲解。第一个单元主要内容是分子图形表现方法 基础,还会介绍制作形象逼真的图像要了解的知识。另外的两个单元是针对高级用户,介 绍了VMD的脚本。尽管非技术性用户可以略去脚本的阅读,但是我们鼓励每个人都去试一 试着读一下,因为它会提供一些有力而易用的工具,这些工具是简单的图形用户界面所无法 提供的。 本教程以一种有趣的小蛋白质泛素的研究为例来说明VMD的应用。在本文中,一些资 料是在小框中出现的。这些小框中包括教程的补充内容,例如泛素扮演的生物学角色,使用VMD的一些提示和捷径等等。 如果你有对本教程的评论和问题,请发邮件至tutorial-l@https://www.360docs.net/doc/0c12639777.html,。邮件列表可以在https://www.360docs.net/doc/0c12639777.html,/Training/Tutorials/mailing list/tutorial-l/.中找到。 泛素本教程会用VMD来显示泛素。泛素是一个由76个氨基酸组成 的小蛋白质,在所有的真核生物中普遍存在。在所有真核生物蛋白 质中,泛素是最为保守的蛋白质之一(在昆虫,鱼,牛和人中,前 74个氨基酸是完全一样的)。它已被证明存在于细胞核、细胞质和 细胞表面。它首要的功能是介导蛋白质降解,在降解过程中,作为 细胞内蛋白水解酶识别的标志。 需要的程序: 以下是本教程中需要的程序 VMD: 可以从https://www.360docs.net/doc/0c12639777.html,/Research/vmd/下载(在所有平台上均可使用)。 绘图程序:要观看从VMD输出的图像,需要专门的程序。VMD有一个内置的绘图程序, 也可以应用外部程序。应用什么程序是由你的操作系统决定的。例如: – Unix/Linux: xmgrace, http://plasma-gate.weizmann.ac.il/Grace/ – Windows: Excel, https://www.360docs.net/doc/0c12639777.html,/en-us/FX010*********.aspx (需要购买) – Mac/Multiple Platforms: Mathematica, https://www.360docs.net/doc/0c12639777.html,/ (需要购买); gnuplot, https://www.360docs.net/doc/0c12639777.html,/(免费下载) 现在开始学习VMD 你可以在VMD-tutorial-files目录里找到本教程的文件。如图1所示的VMD-tutorial-files的 文件和目录

第六章 分子动力学模拟 Molecular Dynamics

第六章 分子动力学模拟 Molecular Dynamics –MD 6.1引言 分子动力学模拟方法是在牛顿力学的理论框架下,根据体系内分子之间的相互作用势,获得每个原子随时间运动的轨迹,通过系综平均,可以得到感兴趣的与结构和动力学性质有关的物理量,如:平均原子坐标,平均能量、平均温度及原子运动的自相关函数等。这些物理量是通过对每个原子的运动轨迹,即微观量求平均而得到的宏观量,因此可以与实验观测量进行比较。 用计算机模拟方法在向空间采样方法有两种: (1) 随机采样 MC (2) 确定性方法MD 以上讲过的MC (Monte Carlo )采样方法就是随机方法,与随机方法不同,确定性方法是按照动力学规律使系统在相空间运动。分子动力学模型就是一种确定性方法。它的基本出发点是从一个完全确定的物理模型出发,通过解牛顿运动方程而得到原子运动的轨迹。我们感兴趣的可测量的客观物理量可以通过相空间的采样求系综平均而得到。在多态历经假设成立的情况下,系综平均与长时间平均是相同的。 ? ∞ →∞==τ τ τ0 1 ))(),((lim dt t p t q A A A 系综 其中q,p 为t 的函数。A 表示系综平均,∞A 表示无穷长时间平均。因模拟时间总是有限的。对耦分子体系,当模拟时间大于分子的弛豫时间时,有限观测时间可以变成为无穷长的。 当弛豫模拟〉τt ,模拟t 可认为∞,因物理上的∞是不可能的。 6.2基本原理 1.动力学方程 基本动力学方程包括在经典力学(CM )框架下的牛顿方程和在量子动力学(QM )框架下的薛定谔方程。在常温下,经典的牛顿方程对研究生物分子体系的结构和动力学性质已经足够了,因为这时体系的量子效应并不十分重要。但是,对研究包含隧道效应的反应时间问题时,量子效应十分明显,这时就必须用QM 方程来模拟体系的量子动力学性质。

高通量筛选神经毒性(Molecular Devices)

高通量筛选神经毒性 优点 完全自动化的图像获取与分析 快速得到每个细胞的多表型参数 实时监测活细胞的毒性,可持续几分钟至几天 神经系统对许多毒性化合物以及自然环境中生成的有害物质非常敏感。在疾病发生过程中,神经毒性可以对大脑或者外周神经系统造成短暂或持续性的损伤,例如脊髓损伤,中风,创伤性脑损伤等。同时这种神经毒性也是造成很多神经退行性疾病诸如阿尔兹海默和帕金森的主要诱因。 诱导人多功能干细胞的高通量成像技术可以用于筛查候选药物或者环境污染物的神经营养,保护功能或者神经毒性大小。本篇说明会阐述如何结合iPSCs,分子仪器和软件自动对诱导多功能干细胞进行终点法及活细胞的神经毒性筛选。 以iPSC为基础的毒性筛查 诱导多功能干细胞技术对我们研究神经元毒性是十分有用的,iPSCs可以大批量的展示成熟神经元的功能。如果将这种独特的生物学相关的细胞类型和高通量成像分析结合在一起,我们就可以快速的筛选出在引起神经元毒性中起主导作用的化合物并大大减少临床前研究和相关动物实验的成本。此篇中用到的是Cellular Dynamics International公司完全分化的人神经细胞。 量化完整的神经细胞网 高通量分析是一种定量化的分析方法,其可以测量神经突触长度表征被测物的阳性或阴性作用。iPSC衍生的神经元细胞可以在3-5天内于96或者384孔板中形成神经元网络,然后用毒性化合物刺激48-72小时。神经网被?-tubulin标记后,可利用ImageXpress? Micro 宽敞成像系统获取图像。和抗抗体我们可以实现神经元网络的可视化。使用MetaXpress? 图像处理软件中Neurite Outgrowth模块和AcuityXpress? 高内涵数据分析软件对相关图像和实验数据进行分析。 无论是否进行了细胞核复染色,Neurite Outgrowth模块都能找到神经细胞胞体,并根据这些荧光标记的神经细胞轴突将之标定为阳性细胞。神经细胞网络具有几个重要的特征参数包括轴突数目,轴突长度,每个细胞或者区域的分支数。我们可以针对每个孔的相关数据和细胞表型进行计算和统计。

细胞活力和细胞毒性的评价(Molecular Devices)

优势:利用SpectraMax i3x多功能微孔板读板机所具有的超灵敏化学发光检测功能进行细胞活力和细胞毒性的评价 简介 方法 准备试剂 ? 仪器具有超高灵敏度化学发光检测功能,最低至10个细胞/每孔;? 微孔板读板高度自动优化设置,可提高检测信号强度? 软件预置模板可以更快分析出检测结果SpectraMax i3x是Molecular Devices公 司最新推出的一款多功能微孔板读板机, 可利用仪器所具有的化学发光检测功能, 进行细胞活力和细胞毒性相应检测。仪器 可灵敏、快速检测出培养基中活细胞的数 目和经相应处理后细胞毒性情况。 Promega公司推出的CellTiter-Glo试剂是 利用了萤火虫荧光素酶反应体系中需要 ATP参与才能使其发光的特点,化学发光 信号强弱取决于培养基中ATP含量的高 低,也就是依赖于其中活细胞数目的多 少。来自于BioVision公司基于生物化学发 光原理的细胞毒性检测试剂盒,目的是检 测腺苷酸激酶(AK)的含量,AK为一种存在 于所有细胞中的常见蛋白,当破坏了细胞 膜完整性后其会释放至培养基中,AK可转 化ADP至ATP,所以可以利用类似方式进 行化学发光检测。 材料 ? CellTiter-Glo Luminescent Cell Viability Assay (Promega P/N G7570) ? Bioluminescence Cytotoxicity Assay Kit (BioVision P/N K312-500) ? HeLa 细胞(ATCC P/N CCL-2) ? 黑色底透 96孔细胞培养板 (Corning P/N 3904) ? 白色96孔细胞培养板(Corning P/N 3917) ? SpectraMax i3x多功能微孔板读板机使用前预先将CellTiter-Glo缓冲液和底物解冻并且平衡其至室温,将CellTiter-Glo 缓冲液加至含有CellTiter-Glo底物的棕色小瓶中,按照试剂盒说明书提示,将试剂轻轻反复颠倒进行混匀。对于生物化学发光细胞毒性检测试剂盒,其中包含了1瓶AK检测试剂,此试剂使用前预先将1.1ml AK试剂缓冲液加入其中并轻轻混匀,需在室温环境下平衡15分钟后使用。这个10X 的AK试剂的储存液需要稀释后才能成为试剂缓冲液。细胞数目与化学发光信号关系Hela 细胞培养在含有10%胎牛血清和双抗的MEM培养基中,细胞经胰酶消化后,使其悬浮于培养基中进行计数。处理后的细胞铺在96孔板中,经细胞培养基稀释后其密度从50,000细胞每孔/100ul至10个细胞每孔/100ul。如果将细胞铺在384孔板时,稀释后密度从12,500细胞每孔/25ul至6个细胞每孔/25ul。对照孔中仅需加入细胞培养基用于检测其背景的化学发光信号值。细胞试验过程中,精确的细胞数目可用于生成标准曲线,将不同体积的CellTiter-Glo试剂加入相应的孔板中,如100ul(96孔板)或25ul(384孔板)。将微孔板放置于 振荡器上轻混2分后,室温条件下孵育10分 钟,等化学发光信号值稳定后再进行检 测。

化学发光法检测细胞活性(Molecular Devices)

介绍 在SpectraMax ? L和SpectraMax ? M5酶标仪上应用Promega CellTiter-Glo化学发光法 检测细胞活性 MD公司的SpectraMax ? L及SpectraMax ? M 5型号酶标仪结合P r o m e g a 公司的CellTiter-Glo化学发光细胞活性检测试剂盒能进行快速灵敏的活细胞数量测定。CellTiter-Glo检测法使用了萤光素酶,需要ATP使其反应发光。发光信号强度由ATP量决定,而ATP的多少取决于活细胞数目。SpectraMax ? L及M5酶标仪均能提供96孔和384孔化学发光检测功能。 方法 准备CellTiter-Glo试剂 使用前将CellTiter-Glo缓冲液和底物在室温中平置解冻。然后将缓冲液倒入装有底物的棕色瓶中,并按照CellTiter-Glo操作手册中指示,温和颠倒瓶子以混匀。细胞计数及产生发光信号 用含10%胎牛血清和L-谷氨酰胺的Ham ’s F12培养基培养CHO-K1细胞。胰酶消化后使细胞悬浮在培养基中,并进行细胞计数。用96孔板检测时,每孔中加入100ul细 作者 Cathy Olsen, Ph.D., MDS Analytical Technologies,1311 Orleans Drive, Sunnyvale, CA 94089.材料: 1.CellTiter-Glo化学发光细胞活性检测试剂盒(Promega公司,货号G7570),包括CellTiter-Glo缓冲液和CellTiter-Glo底物(冻干粉) CHO-K1细胞(ATCC,货号CCL-61)白色96和384孔板(Greiner Lumitrac 200,货号655075和781075)SpectraMax ? L化学发光微孔板检测仪或SpectraMax ? M5多功能微孔板读板机 胞悬液,细胞浓度从50000个/孔稀释到24个/孔。384孔进行检测时,每孔中加入25ul悬液,细胞浓度从12500个/孔稀释到25个/孔。空白孔中加入不含细胞的培养基,用于检测背景光值。 为了确保CellTiter-Glo检测中细胞数量的准确性,细胞不能贴壁和生长,但能及时被检测到。每孔中加入100ul(96孔板)或25ul(384孔板)CellTiter-Glo试剂。然后将微孔板放在振荡器上温和振荡混匀2分钟,室温孵育10分钟,使其产生稳定的发光信号。 制作ATP标准曲线 ATP标准样品用培养基制备,浓度范围从100fmol/孔到1nmol/孔(96孔板),或25fmol/孔到250pmol/孔(384孔板),按上述同样体积加入微孔板中。空白对照孔加入不含ATP的培养基。适量CellTiter-Glo 试剂加入每孔,并按上述步骤孵育。仪器设置和样品分析 检测板用SpectraMax ? L和SpectraMax ? M5酶标仪进行读数,并使用SoftMax ? Pro 软件中预设参数的CellTiter-Glo模板。根据Promega推荐,检测时间设置为1秒。然后在SoftMax ? Pro软件上进行平均发光强度和标准偏差计算,细胞浓度稀释曲线和ATP标准曲线作图。

Molecular Shape

Molecular Shape While Lewis dot structures can tell us how the atoms in molecules are bonded to each other, they don’t tell us the shape of the molecule. In this section, we’ll discuss the methods for predicting molecular shape. The most important thing to remember when attempting to predict the shape of a molecule based on its chemical formula and the basic premises of the VSPER model is that the molecule will assume the shape that most minimizes electron pair repulsions. In attempting to minimize electron pair repulsions, two types of electron sets must be considered: electrons can exist in bonding pairs, which are involved in creating a single or multiple covalent bond, or nonbonding pairs, which are pairs of electrons that are not involved in a bond, but are localized to a single atom. The VSPER Model—Determining Molecular ShapeTotal number of single bonds, double bonds, and lone pairs on the central atomStructural pair geometryShape 2Linear

【专业英语】2-Molecular Weight

Molecular Weight The molecular weight of a polymer is of prime importance in the polymer’s synthesis and application. Chemists usually use the term molecular weight to describe the size of a molecule. The more accurate term is molar mass, usually in units of g mol-1. The interesting and useful mechanical properties that are uniquely associated with polymeric materials are a consequence of their high molecular weight. Most important mechanical properties depend on and vary considerably with molecular weight as seen in Fig. 1-3. 2 There is a minimum polymer molecular weight (A), usually a thousand or so, to produce any significant mechanical strength at all. Above A, strength increases rapidly with molecular weight until a critical point (B) is reached. Mechanical strength increases more slowly above B and eventually reaches a limiting value (C). The critical point B generally corresponds to the minimum molecular weight for a polymer to begin to exhibit sufficient strength to be useful. Most practical applications of polymers require higher molecular weights to obtain higher strengths. The minimum useful molecular weight (B), usually in the range 5000–10,000, differs for different polymers. The plot in Fig. 1-3 generally shifts to the right as the magnitude of the intermolecular forces decreases. Polymer chains with stronger intermolecular forces, for example, polyamides and polyesters, develop sufficient strength to be useful at lower molecular weights than polymers having weaker intermolecular forces, for example, polyethylene. Properties other than strength also show a significant dependence on molecular weight. However, most properties show different quantitative dependencies on molecular weight. Different polymer properties usually reach their optimum values at different molecular weights. Further, a few properties may increase with molecular weight to a maximum value and then decrease with further increase in molecular weight. An example is the ability to process polymers into useful articles and forms (e.g., film, sheet, pipe, fiber). Processability begins to decrease past some molecular weight as the viscosity becomes too high and melt flow too difficult. Thus the practical aspect of a polymerization requires one to carry out the process to obtain a compromise molecular weight—a molecular weight sufficiently high to obtain the required strength for a particular application without overly sacrificing other properties. Synthesizing the highest possible molecular weight is not necessarily the objective of a typical polymerization. Instead, one often aims to obtain a high but specified, compromise molecular weight. The utility of a polymerization is greatly reduced unless the process can be carried out to yield the specified molecular weight. The control of molecular weight is essential for the practical application of a polymerization process.

分子伴侣(molecular chaperones)

分子伴侣 (molecular chaperone) (2018年10月) 分子伴侣(molecular chaperone)是指细胞中某些蛋白质分子可以识别正在合成的多肽或部分折叠的多肽,并与多肽的某些部位相结合,从而协助蛋白质的正确折叠、组装、转运、降解错误折叠及抑制蛋白质聚集,维持正常的蛋白质稳态,本身并不参与最终产物的形成的一类分子。分子伴侣是生物体内普遍存在的一类蛋白质,广泛存在于原核生物和真核生物中。解螺旋 https://www.360docs.net/doc/0c12639777.html, 一、分子伴侣分类 1. 伴侣素家族(Charperonin,Cpn) Cpn家族具有独特的双层7-9元环状结构的寡聚蛋白,它们以依赖ATP方式促进体内正常和应急条件下蛋白质折叠。它又可以分为GroE1(HSP60)家族和Tris家族。GroE1伴侣蛋白ATP依赖性构象变化从而促进底物蛋白质的折叠[1]。GroE1在体内与一种辅助因子,如 E.coli中的GroEs,发挥协同作用。Tris家族没有类似的辅助因子。 2. 热休克蛋白70(HSP70)家族 热休克蛋白(HSPs)其表达受包括热休克、营养缺乏、缺氧、中毒等的不同应激诱导,能够防止蛋白的错误折叠和聚集,维持细胞内稳态[2]。 HSP70家族是进化史上最保守的蛋白质之一,家族成员包括四个:grp78、mtp70、hsc70及hsp70。HSP70同疏水的肽类有高亲和力,并且随着ATP的水解而增高。HSP70与多肽之间的可逆作用在蛋白质的折叠、转运、错误折叠多肽的降解及其调控过程中有着重要的作用。HSP70表达和转录激活主要通过转录激活热休克因子1(HSF1)的作用而迅速调节。RNA聚合酶II启动子近端停顿的转录,受HSP70基因表达的调控。Hsp70是蛋白质稳态的重要参与者,在蛋白质折叠,解聚和降解中具有重要作用。HSP70通过泛素-蛋白酶体系统以及不同的自噬途径(巨自噬,微自噬和分子伴侣介导的自噬(CMA)在底物降解中起重要作用,有助于蛋白质降解[3]。 3. 热休克蛋白90(HSP 90)家族 热休克蛋白90(Hsp90)蛋白家族的成员是高度保守的普遍存在的分子,其分子量约为90kDa。属于分子伴侣,可以促进从头合成或错误折叠的蛋白质的折叠,并抑制蛋白的聚集。HSP90蛋白参与必需的细胞过程和调节途径,如细胞凋亡,细胞周期控制,细胞活力,蛋白质折叠和降解以及信号传导事件。此外,它们通过激活抗原呈递细胞和树突细胞诱导适应性

相关文档
最新文档