Chapter 29: Methods & Tools in Microbial Ecology

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Welcome to the Deep Dive.

Today we're digging into microbial ecology.

It's a field that's just exploded, thanks to new tech, showing us this hidden world of microbes.

Absolutely, and it started with this, well, slightly embarrassing moment for science, you could say.

Right, that idea that the deep ocean floor was sterile.

Claude Zobel, back in 55, said basically nothing lived below 10 meters of seabed.

Yeah, and that idea got a big boost from that whole Alvin submarine incident.

Remember, it sank, sat there for 10 months.

Oh yeah, the sandwich, they pulled it up, and the lunch inside looked almost untouched.

Exactly.

So everyone thought, see, too extreme down there, nothing can even eat a sandwich, which of course wasn't the full picture.

It really highlights how much our understanding depends on the tools we have, doesn't it?

Yeah.

That picture is, well, completely wrong now.

Totally.

Things really started changing in the mid -80s.

The Department of Energy started drilling deep wells, and then that big finding in 94.

Where they found microbes actively growing like 500 meters down in the seabed.

That was the moment.

It kicked off this whole field people sometimes call the deep hot biosphere, and it's crucial stuff.

Because what, potentially half of all microbial life on earth might be down there?

That's the estimate.

It's staggering.

So we're way past asking is there life

now?

Now the questions are more like,

who is actually down there?

How fast are they growing, if L?

And what on earth are they eating?

And tackling those questions needs everything.

It's lab work, trying to grow pure cultures.

But also the high -tech molecular stuff, like digging through all the DNA.

Metagenomics, yeah.

And then you absolutely need the in situ measurements, checking the chemistry right there in the mud or water.

It's truly interdisciplinary.

It has to be.

I mean, think about the numbers.

You might have communities with what?

10 to 10, 17 individual cells, representing maybe 177 different species or taxa.

It's just vast.

Okay, that scale immediately brings up the elephant in the room.

Yeah.

The biggest challenge.

The culturing problem, absolutely.

If we can't grow most of these microbes in a standard lab dish,

how do we even begin to study them?

That's it.

That's the famous great plate count anomaly.

You look under a microscope, you see millions of cells, you put that same sample on a Petri dish.

And almost nothing grows.

Right.

Sometimes less than 5%.

It means we're effectively blind to, you know, 95 % of what's actually living there based on culturing alone.

So those microbes that don't grow on the plate, but we think are still alive, those are the VBNCs.

Viable, but non -culturable.

Yep.

They're alive,

metabolically active maybe, but just won't divide under those specific lab conditions.

So how do you prove they're viable if they won't grow?

You can't just poke them, right?

Yeah, not quite.

We use viability tests.

One common way is with special dyes, like the Live Dead Backlight Kit.

How does that work?

It uses two dyes.

One gets into all cells, lab or dead, makes them glow green.

The other can only get through damaged membranes, so it stains the dead cells red.

Live cells stay green, dead ones turn red.

Okay, that's visual.

What about molecular methods?

I saw something called VPCR, viability PCR.

Yeah, VPCR is pretty neat.

It's a chemical trick.

You add a specific dye before you extract the DNA.

This dye slips into cells with leaky membranes, the dead or dying ones.

Then you hit it with light, and the dye permanently binds to, and basically messes up the DNA inside those dead cells.

Ah, so it cross -links it, making it impossible to amplify later.

Exactly.

So when you then do your PCR amplification, you only amplify DNA from the cells that were intact and alive, the ones the dye couldn't get into.

Clever.

So you filter out the noise from dead cells' DNA.

But sometimes you do need them to grow, right?

To study their physiology.

Definitely.

And that's where enrichment cultures come in.

You try to game the system.

How so?

You tailor the growth medium to favor just one type or one metabolic group from a complex sample while suppressing everything else.

You need a good hunch about what that microbe likes, its niche.

Like the example from Monolake.

They needed very specific conditions.

Right.

Anoxic conditions, using arsenite as the electron donor and nitrate as the acceptor.

Super weird stuff to us, but perfect for that particular bug.

Without that specific recipe, it just wouldn't grow.

And you need patience, too, apparently.

Not everything grows overnight like E.

coli.

Oh, absolutely not.

Some of those soil anaerobes they mentioned needed three months of incubation before they showed any signs of growth.

And some bacteria might even stop dividing before the culture looks visibly cloudy.

So, okay, for the ones that do cooperate and grow, how do we count them reliably, especially in messy environmental samples?

The traditional method, despite its flaws, is the most probable number technique, MPN.

Right, MPN.

It's based on statistics, not direct counting.

Exactly.

You do serial dilutions of your sample, usually tenfold dilutions.

Then from each dilution level, you inoculate multiple tubes, typically three or five.

Okay.

You incubate them, and then you just record the pattern of growth.

Like maybe all three tubes from the $10 dilution grew, only one from 10 -4 grew, and none from 10 -5.

Oh, that gives you a pattern, like 310.

Precisely.

You take that pattern, 310,

look it up in a standard MPN table, and it gives you a statistical estimate of the most probable number of microbes in the original sample after you account for the dilution factor.

What are the catches?

The biggest is that it assumes the microbes are randomly distributed in the original sample, but in nature they often clump together, which messes up the statistics.

Makes sense.

So moving towards more modern, faster methods.

Extinction culture.

That sounds drastic.

It's about dilution again, but really extreme.

You dilute the sample so much that ideally each little culture vessel only gets between one and ten cells.

Ah, so you're basically isolating them by diluting them down to almost nothing.

Kind of, yeah.

It increases the chance of getting a pure or near -pure culture, even if it grows very slowly or doesn't get very dense.

And then there's culturomics.

Sounds like genomics, but for culturing.

It is.

It's a brute force, high -throughput approach.

You basically throw the kitchen sink at the sample.

You test hundreds of different growth media, different temperatures, pH levels, oxygen concentrations, all at once in tiny formats like microplates.

Just trying everything to see if something new will grow.

Pretty much.

Anything that grows gets picked, and then you usually sequence its SSUR RNA gene to figure out what new thing you've managed to coax into culture.

Okay, speaking of high -tech, optical tweezers.

Using lasers to grab single cells?

That sounds like science fiction.

It kind of looks like it too, but it's real physics.

A tightly focused laser beam creates this tiny point of highlight intensity.

And cells get attracted to that.

Yeah, because they're dielectric materials.

They get polarized by the light's electric field and are drawn towards the brightest spot the focus of the beam.

It creates an optical trap.

So you can literally grab one specific cell with the laser.

And move it.

You can physically pick it up and deposit it into, say, a tiny drop of clean media in a micropipette.

Isolate it completely.

Wow.

Very precise.

But I imagine it's slow compared to other methods.

Oh, much slower than something like flow cytometry for sorting, but incredibly precise for targeted isolation.

Which brings us neatly to the other side of the coin.

The vast majority we can't grow easily.

How do we study them?

Right.

If you can't culture them, you go after their molecules directly.

Like molecular forensics.

Starting basic, just counting them.

Yep.

You can use general fluorescent dyes like DAPI or acrydine orange.

They bind to DNA and make all the cells light up under a fluorescence microscope, so you can just count them.

Even tiny things.

Yeah.

Some dyes like SYBR green are so bright they can even make virus particles visible, which is pretty amazing.

Okay.

Counting is one thing, but identifying who they are.

That's where Fi -ish comes in.

Chlorosin in situ hybridization.

Yes.

This is key for identification within a sample.

You design a short DNA probe that's complementary to a specific sequence, usually in the ribosomal RNA.

B -S -S -U -R -N -A.

The barcode gene.

Exactly.

And you attach a chlorescent tag to that probe.

Then you treat the sample to make the cells permeable.

Add the probe.

And it goes inside the cells and sticks only to the matching RNA sequence.

That's the idea.

So only the cells belonging to the specific group your probe targets will light up with that particular color.

But you mentioned a problem slow growing microbes in nature might not have many ribosomes.

So the signal is weak.

That was a major limitation.

If a cell isn't growing fast, it doesn't need many ribosomes, so there aren't many targets for your probe to bind to.

The signal can be too dim to detect reliably.

So how do they fix that?

Cardfish.

Cardfish.

Catalyzed reporter deposition.

This was a huge improvement.

Instead of just a fluorescent tag on the probe, you attach an enzyme like horseradish peroxidase, HRP.

An enzyme.

What does that do?

After the probe binds, you add a special substrate molecule that also has a fluorescent tag.

The HRP enzyme on the probe activates lots of these substrate molecules right near the probe.

So one probe binding triggers a reaction that deposits tons of fluorescent signals right at that spot.

It amplifies the signal massively.

Exactly.

It makes the signal deposition catalytic.

So even if only a few probes bind because ribosome numbers are low, you still get a bright, easily detectable spot.

It lets us see those sluggish environmental microbes.

Very cool.

Okay, moving purely to genetics extracted from the environment, metagenomics.

PCR is the workhorse here for amplifying genes like SSU, rRNA, right?

Absolutely fundamental.

You extract all the DNA from a sample soil, water, whatever, and then use PCR to amplify specific genes you're interested in, like the RNA gene for diversity studies or functional genes.

But PCR isn't perfect, is it?

There's this issue of bias.

Oh, yeah.

PCR bias is a constant headache.

It's not a perfect photocopy machine.

Some DNA sequences amplify much more easily than others.

Why is that?

Several reasons.

Maybe the DNA has a really high G plus C content which makes it harder to melt apart.

Or maybe the cell it came from had a really tough cell wall so you didn't lose it efficiently and get its DNA out in the first place.

Or the DNA could be degraded.

So the final mix of amplified DNA doesn't truly represent the original proportions in the community.

Not exactly.

It's skewed.

You might over -represent the easy -to -lies, easy -to -amplify species.

It's something you always have to keep in mind when interpreting the results.

Right.

Now sometimes, instead of sequencing everything, researchers want a quicker snapshot of diversity, like DNA fingerprinting.

DGGE comes up here.

Penaturing Gradient Gel Electrophoresis.

Yeah.

DGGE gives you a kind of barcode for the community.

How does it work?

You amplify a gene like SSU or RNA from the community DNA.

Right.

So you have a mix of PCR products, all roughly the same size, but with slightly different sequences representing the different organisms.

Okay.

Then you run this mix through a special gel that has a chemical gradient, usually urea and formamide, which causes DNA to denature, to melt apart.

And different sequences melt at different points in the gradient.

Exactly.

The melting point depends heavily on the G plus C content.

Higher G plus C means more stable, melts later.

So as these DNA fragments travel through the gel, they reach a point in the gradient where they start to melt, and that dramatically slows their migration.

So fragments with different sequences stop at different positions, creating a pattern of bands.

Yep.

Each band, ideally, represents a different original sequence type, a different organism.

More bands mean more diversity.

You can compare patterns between different samples easily.

So it tells you about the diversity, but not necessarily who each band represents unless you cut it out and sequence it.

Correct.

It's great for comparing communities quickly, seeing shifts, but doesn't give you identities directly like sequencing does.

And for even faster screening, there are phylochips,

like DNA microarrays for microbes.

Phylochips, yeah.

They're basically glass slides with thousands of tiny spots, each containing a known DNA probe, often targeting specific SSU rRNA sequences or functional genes.

So you label the DNA or RNA from your environmental sample, wash it over the chip.

And wherever it hybridizes to a matching probe on the chip, that spot lights up when you scan it with a laser.

It gives you a very fast readout of which groups or genes are present in your sample.

Okay, that covers identifying who is there.

But that leads to the really big question, maybe the most important one.

What are they actually doing?

Exactly.

This is where we shift focus from identity to activity and function.

How do these microbial communities drive the big biogeochemical cycles, carbon, nitrogen, sulfur that keep the planet running?

And for that, we need different tools again,

like microelectrodes.

Microelectrodes are fantastic for probing microenvironments.

They're incredibly tiny, like two to five micrometers wide at the tip.

So you can actually stick them into things like microbial mats or sediment layers.

Precisely, and measure chemical conditions with very fine spatial resolution, things like oxygen concentration, pH, hydrogen sulfide levels, millimeter by millimeter.

Revealing those dynamic changes, like in microbial mats example.

Yeah, that's a classic.

During the day, the top layer of cyanobacteria are pumping out oxygen through photosynthesis.

The microelectrode shows high oxygen there, which inhibits the sulfate -reducing bacteria deeper down.

But at night?

Photosynthesis stops, oxygen plummets, and the microelectrode shows hydrogen sulfide, produced by those sulfate reducers, diffusing upwards into the previously oxygenated zone.

It's a completely different world chemically, just based on the time of day.

Wow.

And we can also measure activity using radioactive isotopes.

Right.

That's a common way to measure rates, like primary production or respiration.

You add a substrate labeled with a radioactive isotope,

like bicarbonate with carbon -14, H14 -3 -3.

And then you track where that radioactive carbon ends up.

Yep.

You measure how much of it gets incorporated into the microbial biomass over time to figure out the rate of carbon fixation, for example.

Now, related to isotopes, but different.

Stable isotopes are not radioactive, right?

Correct.

Stable isotopes just have different numbers of neutrons, like carbon -12 versus carbon -13, or nitrogen -14 versus nitrogen -15.

They exist naturally.

And organisms sometimes prefer one over the other.

Isotope fractionation.

Exactly.

Biological processes often discriminate against the heavier isotope.

Enzymes might work slightly faster with the lighter one.

So, for example, microbes might preferentially take up $14 over $15.

How is that useful?

By measuring the ratio of heavy to light isotopes, like $15 in different samples, say, in nitrate in the soil versus nitrogen gas produced, you can track the flow of nutrients and figure out which processes are happening.

The difference from a standard ratio is called the delta value.

Okay, that tracks the overall process.

But then there's stable isotope probing, SIP,

that actually links the activity to specific organisms.

Yes.

SIP is incredibly powerful for that exact reason.

It connects who is doing what.

How does it work?

Let's use that rice paddy methanogenesis example.

Okay.

So, researchers wanted to know which microbes were actually eating

and producing methane in rice paddy soil.

They fed the soil sample CO2 dollars that was labeled with the heavy stable isotope, carbon -13 and CO2 dollars.

So, only the microbes actively consuming that CO2 dollars would incorporate the $13 into their cells.

Right.

Into their DNA, their RNA, their proteins, everything.

So, those active secO2 -consuming microbes become physically heavier or denser than the inactive ones.

And you can separate them based on that density difference.

Yes.

You extract the total RNA, for instance, and spin it in an ultracentrifuge with a density gradient.

The heavy 13 -labeled RNA from the active microbes will form a band lower down in the gradient than the normal light 12 -IC RNA from inactive microbes.

And then you just collect that heavy RNA band.

And sequence it.

Usually the ribosomal RNA.

And that tells you precisely which organisms in that case, specific methanogenic archaea, were actively consuming the labeled CO2 tulli, function linked directly to identity.

That's brilliant.

Okay.

This feels like a good transition to the whole metaomics world.

Getting the bigger picture from genes, transcripts, proteins.

Exactly.

The omics cascade.

Metagenomics is the first step sequencing all the DNA.

That tells you the community's potential, right?

What genes they have.

Potential, yes.

Like finding lots of respiration genes in an oxygen -rich coral reef sample or fermentation genes dominating in a gut sample.

It gives you clues about the overall metabolic capabilities.

But potential isn't the same as what's actually happening right now.

For that,

you need.

Metatranscriptomics.

Sequencing the messenger RNA, the mRNA.

Because mRNA is only made when a gene is actively being turned on, being transcribed.

Precisely.

So it gives you a snapshot of gene expression at the time you took the sample.

Which pathways are actually switched on?

What's the catch?

mRNA is notoriously unstable and degrades really quickly.

So sample handling and extraction are critical and technically challenging.

Getting a clean snapshot is tough.

Is there a way to see where specific transcripts are active?

Like F -ASH,

but for mRNA?

There is, actually.

Techniques like ISRT -O -SHASH and situ -reverse transcriptase -fishish.

It tries to detect specific mRNA molecules within cells in their environmental context.

They used it to see which archaea were expressing the MOA gene for nitrification, for example.

Okay.

DNA is potential.

mRNA is expression.

What's the next layer?

Metaproteomics.

Identifying all the proteins present in the sample.

Because proteins are the actual molecular machines doing the work.

Exactly.

This gives you arguably the closest look at the actual function happening at that moment.

What enzymes are active, what structural components are being made.

Sounds powerful, but also incredibly complex.

Oh, the complexity is mind -boggling.

Think about it.

A single gram of pristine soil might contain a billion different types of proteins from all the different microbes living there.

A billion?

How do you even start to analyze that?

It requires serious technology.

Older methods used 2D gel electrophoresis to separate proteins, then cut out spots and identified them with mass spectrometry.

Newer methods use automated multi -dimensional liquid chromatography like 2D NanoLC hooked up directly to tandem mass spectrometry to identify thousands of proteins in one go.

It's a protein census.

Wow.

Okay.

Is there a technique that really pulls it all together, linking the activity and the identity at the single cell level?

Yes.

The gold standard for that is MarFish.

MarFish.

What does the AMA part stand for?

Microautoradiography.

It's an older technique combined with EFEC -ish.

You feed the microbial community a substrate labeled with a radioactive isotope.

The cells that actively take up and metabolize that radioactive substrate become radioactive themselves.

You then overlay the sample with a photographic emulsion like old school film.

And the radiation exposes the film.

Exactly.

Wherever there's an active cell that took up a label, the radioactive decay exposes the silver grains in the emulsion directly above or around that cell, leaving tiny black dots after development.

So the black dots show you which cells were metabolically active with that specific substrate.

Right.

And then you combine that with ISFI.

You perform FAHish on the same sample using fluorescent probes to identify the cells phylogenetically.

Ah.

So you look under the microscope and you can see, for example, a cell that's glowing red from a specific FAH probe and has black silver grains around it from the NAR.

Precisely.

You simultaneously see who the cell is from phy -fluorescence and what it was doing metabolizing the radioactive substrate shown by the black dots.

Activity and identity linked right there at the single cell level in a complex mix.

That really ties everything together.

Okay, that feels like a good place to wrap up this part of the dive.

Yeah, we've covered a lot of ground.

We definitely have.

We went from the huge challenge of just getting microbes to grow in the lab through all the amazing molecular techniques for figuring out who is there even if we can't grow them.

Using things like fish, cardfish, PCR, DGGE, sequencing.

Right.

And then on to figuring out what they're actually doing using microelectrodes, isotope tracing, SIP, the whole metaomics suite, and finally more fish to link identity and function.

The big picture is that shift, isn't it?

From just cataloging diversity who's there to really understanding ecological function.

What are they doing and how does it impact everything else?

Absolutely.

It's about connecting the dots between the microbes and the massive biogeochemical cycles they drive.

And it really highlights how interconnected the fields are now.

You can't really do cutting edge biogeochemistry without molecular tools.

And the molecular data constantly raises new questions for the chemists and ecologists.

It's a feedback loop.

So the ultimate goal isn't just a giant list of species names.

No, not at all.

It's understanding how those billions upon billions of microbes, those different phylotypes contribute to cycling carbon, nitrogen, sulfur, phosphorus,

all the elements essential for life on this planet.

Linking the names to the jobs, basically.

Which leads to a final thought.

We keep hearing that metagenomics, just sequencing all the DNA out there, consistently turns up way more genes, especially from uncultivated microbes, than we ever find in the ones we can grow in the lab.

This microbial dark matter.

Yeah.

The genetic potential we see out there is vast compared to what's represented in our culture collections.

So the provocative question is, what completely new types of metabolism, what biochemical pathways we don't even have concepts for yet, might be hidden inside that dark matter?

Waiting for some clever new culturing trick or technology to finally bring them into the light.

That's the exciting frontier, isn't it?

What secrets are those uncultured majorities still holding?

Something to think about.

Thank you so much for joining us on this deep dive into the microbial world and its methods.

My pleasure.

We hope you found it useful.

Get you on the next one.