Integrating Genomics Throughout the Curriculum, with an Emphasis on

Prokaryotes

Jeffrey D. Newman

Lycoming College

May 20, 2002

The Context for Change

• Lycoming College – Very Traditional Small National Liberal Arts College – 1500 students

• Our Biology Major – highly proscriptive– 2 semester intro bio series– Genetics– Microbiology– Human Physiology– Plant Science– Ecology– At least 1 upper level course

Incorporation of Molecular Biology, Bioinformatics, Genomics

• Phase I (‘97-’99) Intro and core course labs– Intro. Biology – DNA sequence analysis, plasmid prep, transformation,

restriction digest, gel.– Genetics – PCR from cheek cell DNA, cloning into pBS– Microbiology – PCR of unknown’s rRNA gene, sequencing.

• Phase II (’99-’02) Genomics added to many courses– Intro. Biology – shotgun sequencing, HGP conclusions.– Genetics – discussion of microarrays– Microbiology – Microbial Genome Papers– Molecular Biology – Microarrays (thanks to GCAT)

• Project assessment survey – Spring ’01, GCAT Spring ‘02• Phase III (’03 - ?) – New course – Genome Analysis

Genomics in Intro Biology

• Replication PCR DNA sequencing shotgun strategy contig assembly demo.

• In lab, students identify ORFs in pGLO sequence, translate to protein, BLAST search to ID genes.

• Model Organisms• Human Genome Project

– Gene number– Gene complexity– Types of gene products

• Protein Families!– Disease genes

Venter et al., 2001

Genomics in Microbiology

• Students learn DNA sequencing details in lab (for rRNA gene fragment), use of BLAST search, multiple sequence alignment, construction of phylogenetic trees

• Shotgun sequencing method discussed, contig assembly, identification of ORFs demonstrated.

The Genomics Revolution

• Genome sequences allow the following questions to be asked:– How many genes/proteins do we still know nothing about?

– What are the minimal requirements for a “living” organism?

– How has evolution streamlined microbial genomes?

– How are microbes related to each other?

– What are the genomic differences between:• Archaea and Bacteria?• obligate parasites and free-living organisms?• Phototrophic and chemotrophic organisms?• Organotrophic and lithotrophic organisms?• Mesophiles and Thermophiles?• Pathogenic and non-pathogenic strains?

Applications of Microbial Genome Data

• Gene chips/microarrays can detect tens of thousands of specific DNA or RNA sequences– pathogen identification in tissue sample– virulence genes used for prognosis– antibiotic resistance genes for determining best

treatment

• Identification of genes required for pathogenesis will allow targeted drug/vaccine development

• Determination of gene function in “simple” organisms will help understand function of genes in eukaryotes.

• What enzymes might have industrial applications?

Completed Genomes in GenBank

• Aeropyrum pernix• Aquifex aeolicus• Archaeoglobus fulgidus• Bacillus subtilis• Borrelia burgdorferi• Campylobacter jejuni• Chlamydia pneumoniae CWL029• Chlamydia pneumoniae AR39• Chlamydia muridarum• Chlamydia trachomatis D/UW-3/CX• Deinococcus radiodurans• Escherichia coli• Haemophilus influenzae• Helicobacter pylori26695

• Helicobacter pyloriJ99• Methanobacterium thermoautotrophicum• Methanococcus jannaschii• Mycobacterium tuberculosis• Mycoplasma genitalium• Mycoplasma pneumoniae• Neisseria meningitidis MC58• Pyrococcus abyssi• Pyrococcus horikoshii• Rickettsia prowazekii• Synechocystis PCC6803• Thermotoga maritima• Treponema pallidum• Ureaplasma urealyticum

Annotation, sequencing in progress

• Bordetella pertussis• Clostridium acetobutylicum• Clostridium tetani• Lactococcus lactis• Mycobacterium tuberculosis CSU#93• Neisseria gonorrhoeae• Neisseria meningitidis Z2491• Pasteurella multocida• Pyrobaculum aerophilum• Pyrococcus furiosus• Rhodobacter capsulatus• Sulfolobus tokodaii• Streptococcus pyogenes• Vibrio cholerae• Xylella fastidiosa

• Actinobacillus actinomycetemcomitans• Aquifex aeolicus strain VF5• Bacillus anthracis• Bacillus halodurans C-125• Bacillus stearothermophilus C-125• Bartonella henselae• Bordetella bronchiseptica• Bordetella parapertussis• Buchnera aphidicola• Burkholderia pseudomallei• Caulobacter crescentus• Chlorobium tepidum• Clostridium difficile• Clostridium sp. BC1• Corynebacterium Glutamicum

Sequencing in progress

• Corynebacterium diphtheriae• Dehalococcoides ethenogenes • Desulfovibrio vulgaris• Ehrlichia species HGE agent• Enterococcus faecalis V583• Francisella tularensis• Geobacter sulfurreducens• Halobacterium salinarium• Halobacterium sp.• Haemophilus ducreyi• Klebsiella pneumoniae• Lactobacillus acidophilus• Legionella pneumophila• Listeria monocytogenes• Listeria innocua

• Methanococcus maripaludis• Methanosarcina mazei• Methylobacterium extorquens• Mycobacterium avium• Mycobacterium bovis (spoligotype 9)• Mycobacterium bovis BCG• Mycobacterium leprae• Mycoplasma capricolum• Mycoplasma mycoides subsp. mycoides SC• Mycoplasma pulmonis• Nitrosomonas europaea• Nostoc punctiforme• Photorhabdus luminescens• Porphyromonas gingivalis• Prochlorococcus marinus

Sequencing in progress

• Pseudomonas aeruginosa• Pseudomonas putida• Ralstonia solanacearum• Rickettsia conorii• Rhodobacter sphaeroides• Rhodopseudomonas palustris• Salmonella typhi• Salmonella typhimurium• Salmonella paratyphi A• Shewanella putrefaciens• Sinorhizobium meliloti• Shigella flexneri 2a• Staphylococcus aureus NCTC 8325• Staphylococcus aureus COL• Streptococcus mutans

• Streptomyces coelicolor

• Streptococcus pneumoniae

• Sulfolobus solfataricus

• Thermoplasma acidophilum

• Thermoplasma volcanium GSS1

• Thermus thermophilus

• Thiobacillus ferrooxidans

• Treponema denticola

• Vibrio cholerae

• Xanthomonas citri

• Yersinia pestis

Haemophilus influenzae The first genome

• Proof of principle• 1.8 Mbp chromosome, encodes 1703 proteins• Metabolic capability deduced from genes, not

biochemistry

Mycoplasma genitalium the smallest genome

• Obligate parasite – obtains nutrients from host, lacking many metabolic pathways

• 580 kbp chromosome (many bacteria have larger plasmids)• Only 470 protein-coding genes

Mycoplasma mutated 265-350 genes are essential

Minimal Genome Ethical issues

• Microbial engineering - design of custom bacteria for specific tasks – will they spread?– Biological Weapons?– Are we “playing God?”, if so

• is it wrong?• where do we draw the line?

• Answers question “What is life?” from a reductionist perspective– is life now less “special”?– when does life begin?

Methanococcus jannaschiiThe first Archaeon sequenced

• 1.66 Mbp chromosome + 2 plasmids• 62% of 1738 genes are of unknown function.• metabolic genes most similar to bacteria• information flow genes most similar to eukaryotes

Escherichia coli - 38% of genes are of unknown function

• 4.64 Mbp chromosome, 4288 protein-coding genes • despite amount of study, 38% of genes are of unknown function• evidence for acquisition of substantial amount of DNA from

viruses and other organisms

Genomics in Molecular Biology

• Yeast Gene Expression Lab (7 weeks)– student teams choose conditions, predict genes to be

differentially regulated, design PCR primers– RT-PCR– Northern Blot– Microarray (GCAT)

• Yeast cell cycle –microarray paper discussed in class

• Students presented microarraypapers for “final exam”

Genes Induced in Rich Medium

Ratio Gene Name

Protein Name Function

56.5 HTL1 unknown DNA replication & Chromosome Cycle

47 CDC14protein phosphatase

DNA dependent, DNA replication exit from mitosis

46 SEC34 unknownER to Golgi transport, IntraGolgi transport, Retrograde transport

33 REG1protein phosphatase type I

Cell growth/maintenance, repression of transcription

33 ABP1 actin bindingActin cortical patch assembly, Establishment of Cell polarity

31 RNH70 ribonuclease H DNA replication, RNA processing

29 SLU7 unknown mRNA splicing

Genes Repressed By Treatment With Ergosterol

The Assessment Survey

• Conducted April & May, 2001• Concert recordings (legal) offered as incentive!!• 40 Surveys completed • Survey Sections

– Assessment of Experience– Assessment of Content

Knowledge– Assessment of Skills– Assessment of Attitudes/

Opinions

Significant Results

• Of students who had taken Microbiology (n=27) – 56% identified the source of a DNA sequence– 52% identified a protein from its amino acid sequence– 52% retrieved a the cyclin cDNA sequence from Genbank

• 0% of students who had not taken Microbiology (n=13) successfully completed the BLAST search, 15% successfully retrieved a sequence from the database

• Of students who had taken Microbiology but no upper level courses and had not done molecular research (n=11)– 45% identified the source of a DNA sequence– 45% identified a protein from its amino acid sequence– 36% retrieved a the cyclin cDNA sequence from Genbank

Significant Results - Genomics

• Of students with hands-on use of microarrays (Molecular Biology, Medical Genetics – n=9) more students knew– microarrays are used to analyze many genes at once

(89% vs 29%) (P=.02)– the shotgun method is used to sequence genomes

(56% vs 13%) (P=.02)– how to perform a BLAST search (78% vs 26%) (P=.03)– How to translate a nucleic acid sequence

(56% vs 10%) (P<.01)

Survey question

• Microbial genome sequences are useful because...– 8 – understanding of human genes/proteins– 7 – clues to how organisms cause disease– 6 – define evolutionary relationships, adaptations– 3 – antibiotic development– 3 – identification of microbes– 3 – prep for human genome

Good specific comments

• Connie Wilson – “figure out relationships between different species - two species in same environment both adapted to the conditions but in different ways.”

• Jen Leader – “They can be compared to eukaryotes which will aid in structural and functional identification of proteins/genes.”

• Justin Jay – “they provide us with a dictionary of the different genes a microbe has. With this information we can cut and paste different genes into different organisms.”

• Amy Allen – “if people know the sequence for specific microbes they can better determine how those microbes interact with their surroundings ie: bacteria interacting with other bacteria in biofilms.”

• Kim Murray – “They are finding new ways to treat all different kinds of diseases by using genome sequences and they are also establishing new evolutionary relationships. They are also important because they are finding things they thought they never would that will be beneficial in many areas of biology.”

Conclusions

• Exposure to genomics has led to improved understanding of this field

• Students successfully used the NCBI website to perform a BLAST search or retrieve a sequence from the database.

• Students with little to moderate experience using Lasergene did not retain skills.

• New bioinformatics exercises will be based on web-based sources, or downloadable software

Visit the Project Web Page athttp://www.lycoming.edu/~newman/models.html

Thank You to….

• Malcolm Campbell for organizing GCAT

• Other GCAT members for protocols, advice via listserv

• DNAstar for Lasergene software

• Lycoming College Biology Department for encouragement, cooperation, financial support of the Molecular Biology and Bioinformatics Project.

• My students as we participate in thegenomics revolution together!