MIC/MMG 111 MT1

Relative sizes - microbes compared to macroscopic organisms

• 1-50 bac interact w/ 1 human cell

• Bac avg size 1-5µm; 0.01-0.1µm virus; 10-100µm mammalian cells

• 1M microbes/cm² on skin; 1T microbes on skin; 10k microbial sp. on human bod; 8M unique protein-coding genes in human microbiome (~20k human genes);

  • 10:1 microbes: human cells on body

Diversity - microbes compared to macroscopic organisms

• Known: 25 Phyla, ~2k genera, ~5k sp., ~80% metagenome mappability, 316M genes

• Unknown:

  • undetected unknown, hidden taxa & strain-level diversity (~20% sequences not matching microbial genomes),

  • f(x)al unknowns (~40% genes w/o match in f(x)al databases)

• Human gut ecosystem varies by site & ppl

Physiology - microbes compared to macroscopic organisms

• Microbes can break down:

  • O₂, H₂, CO₂, CH₄

  • 1C compounds (methanol, formate,...)

  • SCFAs (2-4Cs) (acetate, lactate,...)

  • Sugars, polymers (starch, cellulose,...)

• Types of microbes associated w/ human bod: aerobic resp, anaerobic resp, fermentation, methanogens, syntrophs

  • ↓ / no O₂ in human microbiome, SO MOSTLY ANAEROBIC MICROBES

Development (time) - microbes compared to macroscopic organisms

• Microbes’ generation time = 20 minutes - day

  • (ppl = 20-30yrs)

• Microbiome ∆s over time in body

Pangenome

collection of genome sequences from many individuals of the same species, used to capture genomic variation and as a reference.

Protocooperation

Both organisms benefit without interdependency (similar to mutualism)

Abiotic Microbial Ecosystem

• physical environ/host

• chem gradients (eg. O₂, pH, [nutri])

• biomolecules (carbs, sugar, lipid proteins, metabolites)

• recycling of nutrients

Biotic microbial ecosystem

• inhabitants & hosts (sp, pop, diversity, abundance)

• producers/consumers/symbionts/viruses

• structured env (biofilms)

• diff types of microbial interactions/food web

Casual fallacy

correlation ≠ causation

Cherry picking

choosing ‘best’ data; not representative of ‘total’ data; not reporting all results, anecdotal evidence

Texas Sharpshooter

post hoc (after the fact) unwarranted explanations/significance to random data/patterns

HARKing

hypothesizing after data is known (tip: HARKing=Hypothesis After)

type of texas sharpshooter

Confirmation bias

ignoring data not in support of hypothesis (also internet algorithms- ‘filter bubble’)

Solution to logical fallacies

• use evidence-based reasoning

• Healthy skepticism

• Ask where info came from//how it was learned

• Discuss & test alt explanations (avoid confirmation bias)

Scientific reasoning

• Hypothesis/Claim= tentative explanation for observed phenomenon (should be testable, can be refuted/falsified)

• Premise= prior data for basis

• Rule= links claim & premise)

• Evidence (in results)

• Interpretation (in relation to the claim)

Empirical falsification

using expt to check whether a claim holds up & being willing to reject it if the results don’t match (process of elimination, NOT repeated verification)

Describe the process of hypothesis “falsification”

1. Pose x hypotheses to explain observation

2. Predict results of ea hypothesis

3. Expt. on ea hypothesis & analyze results

4. Support/refute hypothesis?

5. Repeat until “last hypothesis standing”

Define the elements and purposes of sections of a scientific paper

• Title, Abstract

• Intro

  • Observation= note phenomenon tht poses Q/prob

  • Hypothesis (to explain observation)

  • Prediction (why hypothesis is tested)

• Methods= Expt design

• Results= Data collection, figures

• Discussion= interpret results; refute/support hypothesis?

• Conclusion= claims

Cross sectional studies

• observational

• sample @ specific time w/o follow up

  • Uses: calc freq of dz (prevalence)/ risk factor

Cohort studies

• observational

• track ppl w/ risk factor vs. w/o risk factor over time

  • Uses: Relative risk (RR)= find risk/prob of developing dz in individ w/ risk factor compared to those w/o

  • 2 Types

    • Prospective= follow ppl into future & track who develop dz

    • Retrospective= look into past to see who developed dz

      • Case-Control= compare 2 groups: w/ dz (case) vs. w/o dz (cntrl)

      • Use: Odds ratio= odds of having risk factor if individ has dz

Prospective cohort studies

• observational

• follow ppl into future & track who develop dz

Retrospective cohort studies

• observational

• look into past to see who developed dz

Pre-clinical trials study

• experimental

• use of animals

Clinical trials study

• experimental

• use of people

• determine effect of intervention vs different intervention/placebo

  • phase 1: safety

  • phase 2: efficacy

  • phase 3: confirmation (compare to standard treatment)

  • phase 4: follow up (after approval, track over time)

Randomized controlled trials study

• experimental

• a group of ppl get control vs others receive tested drug/intervention

Batch effects

systematic variations form technical/environ factors (regarding studies)

Technical replicate

replicates a study frm n=1

Biological replicate

replicates a study frm n≥2

Catabolism

• any type of metabolism tht prod E (ex cat. Hormones: adrenaline, cortisol, glucagon)

  • Polymer → monomer (eg. lipase for fat→glycerol+FA, protease for protein→AA, amylase for starch→SS)

  • Hydrolysis= break bonds using H₂O

  • Goal: make ATP (2 ways)

1. Substrate Lvl Phosphorylation (50kJ)

• Glycolysis= Gluc + 2ATP + 2ADP + 2Pi → 2 pyruvate + 4 ATP (net 2 ATP)

• Fermentation= Gluc + 2ADP + 2Pi → 2 lactate + 2ATP (net rxn lactic acid fermentation)

2. Oxidative Phosphorylation by Chemiosmotic Theory (<20kJ)

• Aerobic Respiration= Gluc + 6O₂ + 38ADP + 38Pi → 6CO₂ + 6H₂O + 38ATP

  • 6C gluc → (glycolysis) 2x 3C pyruvate → (TCA) 2x CO₂ + 2x 2C Acetyl-CoA → ETC

• OIL RIG (tip: ox has more O, red has more H)

  • Gluc (e^- donor) → ox to CO₂

  • O₂ (e^- acceptor) → red to H₂O

Substrate Lvl Phosphorylation

• Catabolism → makes ATP

• (50kJ)

• Glycolysis= Gluc + 2ATP + 2ADP + 2Pi → 2 pyruvate + 4 ATP (net 2 ATP)

• Fermentation= Gluc + 2ADP + 2Pi → 2 lactate + 2ATP (net rxn lactic acid fermentation)

Oxidative Phosphorylation by Chemiosmotic Theory

• Catabolism → makes ATP

• (<20kJ)

• Aerobic Respiration= Gluc + 6O₂ + 38ADP + 38Pi → 6CO₂ + 6H₂O + 38ATP

• 6C gluc → (glycolysis) 2x 3C pyruvate → (TCA) 2x CO₂ + 2x 2C Acetyl-CoA → ETC

OIL RIG

• Oxidation Is Loss (of electrons) and Reduction Is Gain (of electrons)

• Gluc (e^- donor) → ox to CO₂

• O₂ (e^- acceptor) → red to H₂O

Chemotroph fermentation

e donor: organic

e aceptor: organic

Chemotroph aerobic respiration (chemoorganotrophy)

e donor: organic

e acceptor: O2

Chemotroph anaerobic respiration (chemoorganotrophy)

e donor: organic

e acceptor: inorganic, (not O₂) (eg. NO₃^-)

Chemotroph aerobic respiration (chemolithotrophy)

e donor: inorganic (H2, NH4)

e acceptor: O2

Chemotroph anaerobic respiration (chemolithotrophy)

e donor: inorganic

e acceptor: inorganic (not O2)

Anabolism

• uses E (ATP) for cell differentiation/growth (ex ana. Hormone: GH, testosterone, estrogen)

• Dehydration synthesis= building polymers (prod H₂O)

Hydrolysis

• catabolism

• breaks bonds by incorporating H2O

Dehydration synthesis

• anabolism

• builds polymers by producing H2O

Chemotrophs are?

Catabolic

Describe the primary composition of life (elements, biomolecules, etc) and relative ratios of components

• Cell Composition

1. Protein 50% (for ribosome, AA metab, glycolosis, transport, …)

2. RNA 20%

3. Polysacc 10%, Lipid 10%

4. DNA 3%

• Cell comp is conserved → central metab also conserved

Minimal essential components for cellular growth

C source (hexoses = glucose, fructose, dextrose, sucrose), essential AAs, vits, minerals, and growth factors

Contrast fermentation and respiration (e^- donors, acceptors, products, substrates, ATP yield).

• Respiration= ↑↑↑ efficiency, but need E to run

  • ~18–20x > ATP but is slower than fermentation

  • Can’t use ETC when ↓ [e^- acceptor]/↓ ETC enz/↓ enz activity (alt. Is to do glycolysis/ferment)

• Fermentation= slow, but doesn't need as much E

	Aerobic Resp	Anaerobic Resp	Fermentation
Input/e- donor (substrate)	Gluc	Gluc	Gluc
Terminal e- acceptor (substrate)	O2	Not O2 (eg. nitrate, sulfate,…)	Pyruvate (→lactate) Acetaldehyde (→ ethanol) …
Product	CO2 + H2O	CO2 + red. Inorganic cmpnd	Lactate Ethanol
Modules	Glyc (SLP), TCA, ETC (OxP)	Glyc (SLP), TCA, ETC (OxP)	Glyc, fermentation (SLP) (NO ETC!)
Net ATP/NADH	36-38 ATP	<36 ATP	2ATP/2NADH
ex	Human cells, yeast/bac	bac/arch	Lactate ferm: humans/bac Ethanol ferm: yeast/bac

Impacts of oxygen on metabolism in various types of microbes

• O₂ can be toxic by partial reduction to form free radicals

  • Aerobes have enz (catalase, superoxide dismutase) to detoxify O₂^- radicals

  • Anaerobes do NOT have these enz

Fermentation (typical)

E-yielding rxns tht convert carbs/sugars → acids/-OH/CO₂ w/o O₂

• Usually make ATP thru SLP (by anaerobic redox processes)

• x types of fermentation tht all use gluc but prod diff product (used by diff microbes)

  • Pathways are named after product

• Substrates: ex. Starch, (hemi)cellulose, mucin, sugars, FA, proteins

  • Mucin-degraders= microbes common in gut (bc gut has ↑ mucin)

• Product: ex. SCFA, acids, -OH, aldehyde, gasses 

  • Lactic acid bacteria= fermentative microbes tht prod lactic acid

  • Growth medium w/ gluc & pH indicator show red→yellow when ↓pH

• ↓ [products] intracellularly bc theyre excreted out of cell

Ethanol fermentation

Net: Gluc + 2ADP + 2P_i → 2 ethanol + 2CO₂ + 2 ATP

Types of Fermentation

• Linear= 1S→2P

• Branched= 1S→2P (S acts as donor AND acceptor) (ex: lactate → acetate & propionate)

• 2-substrates= 2S→2P, but the pathways are linked/paired

  • Stickland Rxn= 2-substrate (paired) fermentation of AAs (can be reversible)

    • Pairs of AAs are used (1 as donor & ther other as acceptor)

    • If ↓[C], can start fermenting AAs →SCFAs

    • Substrate ex: proteins, peptides, AAs

    • Product ex: SCFA, phenols, indol, NH₃, N₂

Dismutation= 1S→2P, but S is switched @ the beginning

Use Fermentation when…

• Resp is limited due to ↓ terminal e^- acceptor OR ↓ETC activity

• Lack ETC (Obligate fermenters) (live in anaerobic environ)

• ↑ competition for food (ferment prod ATP fast)

• Wrong environ conditions (eg pH too ↑)

Cellular material for identification of microbes

• Microscopy: microbial phenotype, colonization patterns

• Culturing: sp characterization, cellular f(x)

  • Selective enrichment technique

Genetic material for identification of microbes

• Metabarcoding (=ssu rRNA analyses)

• Metagenomics: genomics, gene f(x)

• Metatranscriptomics: RNA, gene f(x)

  • Use rRNA as phylogenetic markers

Metabolic pathways for identification of microbes

• Metaproteomics: protein expression, metabolic f(x)

• Metabolomics: metabolite prod

Rationale for use of ssu rRNA as a “proxy” for organism phylogeny

• ssu rRNA (small subunit ribosomal RNA)= conserved; can attach known primers to identify variation

  • All organisms have ribosome

• phylotypes/sequence types= groups of organisms classified tgthr based on genetic similarity

Steps in ssu rRNA analysis of a single microbe

1. Obtain microbial comm/ culture/cell

2. Extract comm DNA

3. PCR specific gene

4. Sequence & compare rRNA gene sequences

5. Generate tree→ types/abundance of microbes

Why do Cultivation-independent approach for microbes?

• Some cant be isolated

• Need to know some info b4 you can actually culture them

• Reliance on cultivation for quantification/phylogeny not always accurate

• Want to observe in situ

Alpha diversity

• microbial diversity (sp. richness) W/IN SAMPLE

• sp richness= # sp in sample

• sp eveness= compare rel abundance of sp.

  • dominance= the most abundant sp in microbial comm

• ASVs= phytotypes tht represent exact, unique DNA sequence (100% identical)

• OTUs (operational taxonomic unit)= phylotype where sequences are clustered tgthr based on similarity threshold (usually ≥97%

• Qualitative: how many sp in comm? (presence/absence only)

• Quantitative: accounts for evenness (considers rel abundance) 

• Plots

  • Shannon Diversity Index= compare diversity (richness>evenness) 

  • Simpson’s Diversity Index= compare diversity (evenness (dominant sp)>richness)

    • Less sensitive to sp richness (rare taxa)

    • Rarefraction curves= plot OTUs/ASVs (richness) by # sequence analyzed

Beta diversity

• quant compare diversity BTW SAMPLES

• Qualitative: how many shared sp in comm? (presence/absence only)

• Quantitative: compares dominant sp in comm (considers rel abundance)

• Plots/Stats

  • PCoA= simplify data to fewer D by principal components (PC)  

    • closer together = similar diversity; more closely related

    • PC# shows % of explained variation 

  • Bray-Curtis dissimilarity= stat for diversity comp diffs

    • Approach 1 when all sp in common

    • 1= no sp in common

  • Unifrac distances= turns ea comm’s microbial comp into phylogenetic summary of diversity

    • Allows comparisons b/w samples using clustering & PCOAs

    • → allow to see which communities are more similar/diff

Shannon/simpson’s diversity index increase correlates to

diversity increase