18.3.1 Microbial Metabolism in the Deep Subsurface

Measuring the rate that a microbial function occurs is essential for determining how the function contributes to the carbon cycle. Older methods to study microbial activity in the deep biosphere, such as the incorporation of radioactive thymidine into bulk samples, have largely fallen out of favor since they are insufficiently sensitive to detect microbial activities below a few meters deep into sediments (Reference Cragg, Harvey, Fry, Herbert and Parkes88). A more sensitive method for estimating in situ microbial activity is to measure the turnover rate of trace amounts of radioactive nutrients such as electron donors/acceptors. Such methods have attained widespread use in subsurface environments and have shown that SO₄^2– and CO₂ serve as important electron acceptors for deep subsurface biosphere respiration (Reference Orcutt, LaRowe, Biddle, Colwell, Glazer and Reese89). In agreement with this, DNA signatures for microbes capable of these types of respiration have been identified in many subsurface locations (e.g. Reference Purkamo, Bomberg, Kietäväinen, Salavirta and Nyyssönen90,Reference Durbin and Teske91). Although it may seem that better oxidants should correspond to faster organic matter degradation, recent work has suggested that the rate of carbon remineralization operates independently of which oxidant is available (Reference Beulig, Røy, Glombitza and Jørgensen92). Here, radiotracer-measured rates of carbon oxidation to CO₂ were constant, whether sulfate or CO₂ was the terminal electron acceptor.

Direct microscopic assessment is often uninformative about either taxonomy or physiology because cells tend to be small (Reference Braun, Morono, Littmann, Kuypers, Aslan and Dong93,Reference Baker, Comolli, Dick, Hauser, Hyatt and Dill94) and their morphology does not indicate their identity or environmental functions (Reference Parkes, Cragg, Bale, Getliff, Goodman and Rochelle2). In recent years, SIP coupled to fluorescence in situ hybridization (FISH) and nanoscale secondary ion mass spectrometry (NanoSIMS) has enabled the direct metabolic assessment of natural populations incubated ex situ, but still within their natural microbial community. SIP works on the principle that organisms taking up isotopically labeled substrate will retain it in their biomolecules and can later be identified. After 9 and 405 days of seafloor incubation of a sediment core with ¹³C-labeled glucose, Takano et al. (Reference Takano, Chikaraishi, Ogawa, Nomaki, Morono and Inagaki95) found that subsurface archaea incorporate fresh glucose in the glycerol headgroups of their membrane lipids, but rely on detrital carbon recycling for the hydrocarbon isoprenoid groups of the lipids. FISH allows the microscopic identification of microbes of a particular taxonomic group by attaching fluorescent probes to short DNA sequences that match the taxonomically informative ribosomal RNA present in cells (Reference Amann, Fuchs and Behrens96). In places with low activity, such as the deep subsurface, the dim fluorescence signals of FISH often require amplification with catalyzed reporter deposition (CARD) (Reference Pernthaler and Amann97). NanoSIMS sputters a cesium ion beam across an area of a few micrometers to detect any isotopic label taken up by the microbe during the SIP incubation. Therefore, when combined with FISH, NanoSIMS SIP gives information about what substrates were consumed by which taxonomic groups of organisms on a nearly single-cell basis.

In 2011, Morono et al. used NanoSIMS SIP with CARD-FISH to show that cells in up to 460,000‑year-old sediments, ~200 m deep into the sub-seafloor, were capable of growing on glucose, pyruvate, and amino acids (Reference Morono, Terada, Nishizawa, Ito, Hillion and Takahata98). In addition, acetate and bicarbonate were incorporated into the biomass, although they did not promote growth. However, whether the identity of the cells that grew in these experiments reflected the community present at the time of sampling was not assessed, since only a subset of the growing cells hybridized to FISH probes (Reference Morono, Terada, Nishizawa, Ito, Hillion and Takahata98). This could be the result of either mismatches to the probe DNA sequences or difficulties of hybridizing cells during CARD-FISH (Reference Lloyd, May, Kevorkian and Steen99,Reference Buongiorno, Turner, Webster, Asai, Shumaker and Roy100).

In one of the deepest sub-seafloor drilling operations to date, researchers on Integrated Ocean Drilling Program (IODP) Expedition 337 found relatively high numbers of microbial cells whose taxonomic identities resembled terrestrial communities in 2‑km-deep coal beds, suggesting that these cells had persisted through the burial of these terrestrial sediments over tens of millions of years (Reference Inagaki, Kubo, Bowles, Heuer, Ijiri and Imachi101). By combining SIP, CARD-FISH, and NanoSIMS, Trembath-Reichert et al. found that these communities incorporated methylated compounds into the biomass, sometimes with concomitant methane production (Reference Trembath-Reichert, Morono, Ijiri, Hoshino, Dawson and Inagaki102). Ijiri et al. combined clumped isotopic measurements and label turnover rates to show that deep fluids stimulate substantial methanogenesis at mud volcanoes (Reference Ijiri, Inagaki, Kubo, Adhikari, Hattori and Hoshino103).

An analogous method to SIP that allows single-cell analysis without requiring an expensive NanoSIMS instrument is called bio-orthogonal noncanonical amino acid tagging (BONCAT) (Reference Hatzenpichler, Scheller, Tavormina, Babin, Tirrell and Orphan104). In this method, natural samples are incubated with an amino acid mimic equipped with a functional moiety that can react with a fluorophore after the incubation has ended. In this way, the microbial cells that were making new proteins (and therefore incorporated the amino acid mimic) fluoresce under a microscope and can be counted by eye or physically separated in a flow cytometer for downstream biomolecular study. BONCAT was used in subsurface samples to show stimulation of amino acid incorporation in microbial aggregates incubated with methane (Reference Hatzenpichler, Connon, Goudeau, Malmstrom, Woyke and Orphan105).

Metabolism can also be controlled by entering an inactive or dormant state. Among cultured bacteria, the Firmicutes and Actinobacteria are capable of forming endospores that can withstand low nutrients and inhospitable conditions for long time periods. These properties make sporulation a potentially advantageous phenomenon for deep subsurface life; however, it is possible that common DNA analyses miss spores since they can be difficult to lyse. Therefore, Lomstein et al. measured dipicolinic acid, a key spore coat protein, in the deep subsurface of the Peru Margin to estimate that spores in this deep subsurface environment may be as numerous as nonsporulated cells and the necromass from other dead cells that may provide food for metabolically active microbes (Reference Lomstein, Langerhuus, Hondt, Jørgensen and Spivack40). However, when the decrease in cellular biomass over sediment age is instead used to estimate the microbial necromass production rates, the rate is far outstripped by organic matter buried from ancient pelagic sedimentation (Reference Bradley, Amend and Larowe106).

In marine sediments with low organic matter contents and deep terrestrial aquifers, the radiolysis of water may provide microbial food. Natural radioactive decay of Earth’s minerals can slowly split water into H₂ and oxidized moieties (Reference Lin, Hall, Lippmann-pipke, Ward, Lollar and Deflaun107). Hydrogen production from Earth’s background radiation may seem inconsequential relative to the power provided by sunlight in surface environments. However, H₂ production rates from water radiolysis have been shown to be sufficient to support life in the deep subsurface (Reference Chivian, Brodie, Alm, Culley, Dehal and DeSantis52,Reference Lin, Hall, Lippmann-pipke, Ward, Lollar and Deflaun107,Reference Blair, D’Hondt, Spivack and Kingsley108). The deep subsurface may have additional sources of energy such as serpentinization, which produces the microbial substrate H₂ and has been shown to support many microbial communities (Reference Ménez, Pasini and Brunelli109,Reference Suzuki, Wu, Cheung, Tenney, Wanger and Kuenen110). Serpentinization also produces a large amount of alkalinity, which inhibits autotrophy by pushing carbonate equilibrium away from CO₂. Therefore, unique types of methanogens have been discovered in serpentinizing systems that have novel mechanisms for ameliorating CO₂ limitation (Reference Brazelton, Schrenk, Kelley and Baross111,Reference Lang, Früh-Green, Bernasconi, Brazelton, Schrenk and McGonigle112).

A feature that may be very important to subsurface ecosystems is symbiotic relationships. Historically, microbial communities from deep subsurface aquifers have been studied by examining the cells that are caught on a 1.2‑µm filter, but recent work has shown that a wide range of ultrasmall bacteria pass through these filters (Reference Wrighton, Thomas, Sharon, Miller, Castelle and VerBerkmoes4). These cells form previously undiscovered branches on the tree of life called candidate phyla radiations (Reference Hug, Thomas, Brown, Frischkorn, Williams and Tringe113). In addition to having extremely small cell sizes (0.009 ± 0.002 µm³), they have very small genome sizes as well, and they lack many features thought to be important to free-living organisms (Reference Wrighton, Thomas, Sharon, Miller, Castelle and VerBerkmoes4). In addition, their cell structures show that they have cellular appendages that might aid in cell-to-cell communication, similar to those of ultrasmall uncultured archaea called archaeal Richmond Mine acidophilic nanoorganisms (ARMAN) (Figure 18.4) (Reference Baker, Comolli, Dick, Hauser, Hyatt and Dill94). Therefore, these candidate phyla radiations have been proposed to be obligate symbionts of larger microbes (Reference Wrighton, Thomas, Sharon, Miller, Castelle and VerBerkmoes4).

Figure 18.4 Cryo-electron tomographic reconstruction of ARMAN archaea (Ar), Thermoplasmatales (Tp), vacuole (Va), and virus (Vi). (a) shows the larger image, with a 300‑nm scale bar, and (b) shows the inset, with a 50‑nm scale bar.

Image reproduced from (Reference Baker, Comolli, Dick, Hauser, Hyatt and Dill94).

18.3.2 Predicting Functions of Novel Genes

Many of these genes in subsurface organisms cannot be accurately annotated by their homology to characterized gene products, since most of the latter come from microbes in pure culture (Reference Rinke, Schwientek, Sczyrba, Ivanova, Anderson and Cheng114). Given that genomic data are quickly becoming the most accessible type of data to shed light on deep biosphere communities (Section 18.2), the inability to interpret the functions of much of their genomes is a major limitation. For instance, from its genome and phylogeny, Desulfurivibrio sp. appear to be anaerobic sulfate reducers. However, when they were obtained in pure culture, they did not reduce sulfate, but instead oxidized it (Reference Thorup, Schramm, Findlay, Finster and Schreiber115). A genome from an uncultured phylum contained a homolog of the methyl coenzyme M reductase gene, from which one might conclude that it performs methanogenesis or anaerobic methane oxidation. However, enrichments of this organism could not perform methane metabolisms, but instead oxidized butyrate anaerobically (Reference Laso-pérez, Wegener, Knittel, Widdel, Harding and Krukenberg116).

One method for overcoming difficulties in accurate annotations of genes in organisms that cannot undergo phenotypic ground-truthing is to amplify target genes of interest directly from natural samples or single-cell genomes, ligate them into DNA plasmid vectors, transform them into Escherichia coli, express them as proteins, purify them, solve their structures, and characterize their activities. A predicted gene annotated as a peptidase in the uncultured phylum Bathyarchaeota was heterologously expressed in E. coli and crystallized in order to determine its structure and catalytic activity (Reference Michalska, Steen, Chhor, Endres, Webber and Bird117). Although the gene was annotated as an S15 peptidase with substrate specificity for terminal proline residues, the expressed enzyme, called bathyaminopeptidase, was found to have a much higher affinity for terminal cysteine residues. This distinction illustrates the limitation of inferring enzyme function from homology to known proteins in these uncultured deep subsurface microbes. Homologs of the gene for the II/III form of Rubisco, a well-studied key gene for CO₂ fixation in the Calvin–Benson–Bassham cycle, occur in the candidate phyla radiation among the bacteria in deep terrestrial aquifers. This enzyme had previously only been found in cultured archaea, so its presence in uncultured phyla of deep subsurface bacteria suggested that perhaps it had different catalytic properties in these unknown groups (Reference Wrighton, Thomas, Sharon, Miller, Castelle and VerBerkmoes4,Reference Kantor, Wrighton, Handley, Sharon, Hug and Castelle118). However, adding the Rubisco II/III gene from the candidate phyla radiation lineage to a phototroph, Rhodobacter capsulatus, which had been engineered to remove its native Rubisco gene and had therefore lost its CO₂ fixation capabilities (Reference Smith and Tabita119), caused its full CO₂ fixation capabilities to be revived (Reference Wrighton, Castelle, Varaljay, Satagopan, Brown and Wilkins59).

The limitation of this heterologous gene expression approach is that it has much slower throughput than genetic characterizations. However, it provides hard evidence for function that is lacking when simply inferring enzymatic functions from homology to known proteins. In addition, it presents opportunities for discovering novel functions rather than making assumptions based on previously characterized proteins.

18.3.3 Cellular Bioenergetics

Overcoming energy limitation is a major focus of life in both marine and terrestrial subsurface environments (Reference Parnell and McMahon11,Reference Hoehler and Jørgensen14). Reaction transport modeling of oxygen and nitrate concentration profiles with sediment age showed that deep subsurface communities in the South Pacific Gyre operate at extraordinarily low metabolic rates (Reference D’Hondt, Spivack, Pockalny, Ferdelman, Fischer and Kallmeyer85,Reference Røy, Kallmeyer, Adhikari, Pockalny, Jørgensen and D’Hondt86). Subsurface microbes are therefore operating in a low energy state, and the majority of these populations may be in a long-term stationary stage in which they require energy only for cell maintenance (Reference Lever, Rogers, Lloyd, Overmann, Schink and Thauer120,Reference Jørgensen and Marshall121). Determining the minimum value for cellular maintenance is difficult, but nanocalorimetry, in which the kinetics and thermodynamics of very small populations of cells can be measured (Reference Robador, Larowe, Finkel, Amend, Nealson and Booth122), and long incubations with no new substrate additions (Reference Timmers, Gieteling, Widjaja-Greefkes, Plugge, Stams and Lens123–Reference Kevorkian, Bird, Shumaker and Lloyd125) hold promise for studying organisms operating at very low energies. At the very minimum, living cells must replace biomass fast enough to overcome abiotic racemization rates, which can be very slow (Reference Steen, Jorgensen and Lomstein126,Reference Onstott, Magnabosco, Aubrey, Burton, Dworkin and Elsila127). Determining true growth rates for such natural microbial populations outside of carefully controlled laboratory conditions is nearly impossible because the change in the number of cells over time represents the product of growth rate minus death rate. However, total population turnover rates can be determined (Reference Hoehler and Jørgensen14). Braun et al. used racemization rates to estimate total population turnover times of up to tens of years for marine sediment microbes in relatively organic-rich parts of the ocean (Reference Braun, Mhatre, Jaussi, Røy, Kjeldsen and Seidenkrantz17). Slow biomass turnover times of several months to over 100 years have also been measured by measuring uptake of deuterated water (Figure 18.5) (Reference Trembath-Reichert, Morono, Ijiri, Hoshino, Dawson and Inagaki102).

Figure 18.5 Generation times for microbial life in 2-km-deep sub-seafloor coal and shale beds based on uptake rate of either ²H-labeled water or ¹⁵N-labeled compounds as described in the graph’s key

(adapted from Reference Trembath-Reichert, Morono, Ijiri, Hoshino, Dawson and Inagaki102).

One challenge to such research is the difficulty in making accurate absolute quantifications of specific microbial populations, not just total cell counts, in natural samples that can have very low biomasses or features that disrupt quantification methods. For instance, marine sediments themselves can obscure quantifications with FISH and quantitative polymerase chain reaction (Reference Lloyd, May, Kevorkian and Steen99), and extremely small cells might be missed during filtration of water samples (Reference Baker, Comolli, Dick, Hauser, Hyatt and Dill94). However, a method that accurately quantifies the absolute cellular abundance of particular taxonomic groups in natural deep subsurface samples has yet to be developed.

18.4.1 Extreme Molecular Biophysics

The structures, interactions, and functions of biological macromolecules are highly sensitive to temperature, pressure, pH, salinity, and the concentration of small osmolytes. Take, for example, proton/sodium-coupled electron transfer (PCET) processes, which are central to energy production. The molecular machinery for H⁺-coupled ATP synthesis is essentially the same across most living cells; ATP synthesis succeeds regardless of physical conditions, even though the chemistry of H⁺-driven processes in biological macromolecules is highly sensitive to pressure, temperature, and salinity. The adaptive mechanisms for PCET under extreme conditions are unknown. Likewise, the physical properties of both the proteins and nucleic acids that drive the central dogma are highly sensitive to temperature, pressure, pH, and salinity, and yet DNA transcription and translation succeed even in extreme environments. The importance of understanding the molecular mechanisms of adaptation of fundamental biochemical processes to extreme conditions cannot be overstated. Somehow, in these extreme environments, adaptations take place so that the essential processes necessary to sustain life can proceed unimpeded.

Whereas structure–function–thermodynamics relationships in proteins from thermophiles have been studied extensively, studies on the adaptation to high pressure are limited (Reference Cavicchioli, Thomas and Curmi130). Notable exceptions are pressure-adapted RNA polymerases (Reference Kawano, Nakasone, Matsumoto, Yoshida, Usami and Kato131), metabolic enzymes (Reference Kasahara, Sato, Tamegai and Kato132–Reference De Vos, Xu, Hulpiau, Vergauwen and Van Beeumen138), the bacterial chromosome organizer, histone-like nucleoid structuring proteins (Reference Jian, Xu, Gai, Xu and Xiao139), G-protein-coupled receptors in deep-sea fish (Reference Siebenaller140,Reference Siebenaller and Garrett141), and single-stranded DNA binding proteins (Reference Chilukuri, Bartlett and Fortes142). In addition to identifiable adaptations at the level of the protein’s primary sequence, pressure adaptation at the cellular level has been shown to involve changes in gene expression (Reference Boonyaratanakornkit, Miao and Clark143), such as upregulation of specific transport proteins of the outer membrane protein (OMP) family (Reference Simonato, Campanaro, Lauro, Vezzi, D’Angelo and Vitulo144,Reference Campanaro, De Pascale, Telatin, Schiavon, Bartlett and Valle145) and the production of osmolytes (Reference Samerotte, Drazen, Brand, Seibel and Yancey146–Reference Bartlett149), chaperones (Reference Campanaro, Treu and Valle150,Reference Cario, Jebbar, Thiel, Kervarec and Oger151), polyamines (Reference Nakashima, Yamagami, Tomikawa, Ochi, Moriya and Asahara152), and modified lipids (Reference Bartlett149,Reference Campanaro, Treu and Valle150,Reference Michoud and Jebbar153–Reference Jebbar, Franzetti, Girard and Oger155) (Figure 18.6).

Figure 18.6 Mechanisms of pressure adaptation.

Biophysical aspects of adaptation to extreme environments are poorly understood, although the effects of extreme conditions on mesophilic organisms have been studied extensively. Pressure can modulate the conformation of lipid bilayers, nucleic acids, and proteins (Reference Winter and Dzwolak156). In the case of nucleic acids, structures can be either stabilized or destabilized by pressure (Reference Macgregor157), although in general, RNA and DNA molecules exhibiting tertiary structures, such as hairpins, quadruplexes, and ribozymes, are disrupted by pressure (Reference Fan, Shek, Amiri, Dubins, Heerklotz and Macgregor158,Reference Amiri and Macgregor159). Lipid bilayers are compressed and thickened in response to pressure and become much less dynamic. The melting temperature for gel to liquid crystalline transitions increases with pressure, and organisms living at high pressures are known to have a higher proportion of unsaturated lipids in their bilayers to maintain an appropriate degree of fluidity.

It has long been known that hydrostatic pressure leads to protein unfolding (Reference Bridgman160) and oligomer dissociation (Reference Weber161,Reference Schmid, Ludemann and Jaenicke162). Pressure effects on protein structure arise from differences in molar volume between different conformational states. The molar volume of the unfolded states of proteins (U) is generally smaller than that of their folded states (F) (Figure 18.7), as is the molar volume of monomeric subunits compared to oligomeric species. Pressure shifts the folding/association equilibria toward the state that occupies the lowest molar volume: the unfolded or dissociated states. The values of these volume changes are quite small, typically <150 mL/mol for the unfolding of small globular proteins and <300 mL/mol for the dissociation of oligomers.

Figure 18.7 Schematic diagrams of a folded (a) and unfolded protein (b), in this case the pp32 leucine-rich repeat protein

(adapted from Reference Fossat, Dao, Jenkins, Dellarole, Yang and McCallum163). Cavities in (a) were calculated with a 1.4‑Å sphere using HOLLOW (Reference Ho and Gruswitz164).

Although the differences in volume between conformational or oligomeric states of proteins have been well known for some time (Reference Royer165,Reference Smeller, Biology and Smeller166), their structural origins remained obscure and were hotly debated until recently. It has been shown repeatedly that substitution of a large hydrophobic amino acid side chain such as leucine, isoleucine, or even valine by a smaller one such as alanine or glycine invariably leads to a larger overall magnitude of the volume change of unfolding and to greater sensitivity to pressure (Reference Font, Benito, Lange, Ribo and Vilanova167–Reference Ando, Barstow, Baase, Fields, Matthews and Gruner169). A very strong correlation exists between the volume change of unfolding and the packing density (fractional void volume) of a given protein.

The destabilization of any given protein by pressure is larger at low temperatures. Chen and Makhatadze proposed that hydration not only does not cause pressure-induced protein unfolding, but actually makes a strong contribution that opposes pressure-induced unfolding (Reference Chen and Makhatadze170). However, as temperature increases, the increase in internal void volume becomes smaller than the effects of hydration, and thus the compensation effect diminishes and the overall difference in molar volume between folded and unfolded states diminishes (Reference Chen and Makhatadze171), and can even change sign.

Many aspects of the thermodynamic and structural pressure effects on proteins and adaptations to high-pressure environments remain unknown. It was recently shown that there is no pressure-specific “piezolytes” (i.e. there are no specific volumetric effects associated with low-molecular-weight osmolytes). Rather, their effect is simply to stabilize folded proteins against all manner of perturbations, not specifically high hydrostatic pressure (Reference Papini, Pandharipande, Royer and Makhatadze172). It is not well understood whether there are inherent, specific physical attributes of proteins and nucleic acids that allow them to tolerate high-pressure environments. On a larger scale, the ensemble of different organisms in a given environment may modulate biomolecular adaptation through the physical properties of the biomolecules. Large-scale structural adaptive differences may even be identifiable through comparison of whole genomes.

The populations of folding intermediates and low-lying alternative states implicated in the function, degradation, or aggregation of proteins from piezophiles may be different from those of their mesophilic homologs (Reference Akasaka173,Reference Akasaka, Kitahara and Kamatari174), Thus, proteins from piezophiles may have evolved to modulate the population of such species.

Thankfully, through sustained progress in instrumentation for fundamental physicochemical studies of the effects of pressure on biological molecules, the biophysics community is well positioned to address outstanding issues in biomolecular adaptation. High-pressure nuclear magnetic resonance (NMR) measurements, once restricted to a few centers with specialized equipment (Reference Jonas175–Reference Kremer, Arnold, Brunner, Schuler, Jaenicke, Kalbitzer and Winter178), have been adapted for low cost and ease of use with high-field NMR spectrometers (Reference Flynn, Milton, Babu and Wand179,Reference Peterson, Nucci and Wand180). High-pressure small-angle X-ray and neutron scattering devices are available at several facilities in Japan (Reference Fujisawa, Kato and Inoko181), Europe (Reference Krywka, Sternemann, Paulus, Javid, Winter and Al-Sawalmih182), and in the United States (Reference Ando, Barstow, Baase, Fields, Matthews and Gruner169). Fluorescence, Fourier-transform infrared spectroscopy, and ultraviolet–visible spectroscopy have long been used in high-pressure biophysical research, and electron paramagnetic resonance and circular dichroism spectroscopy have recently been adapted (Reference McCoy and Hubbell183,Reference Lerch, Horwitz, McCoy and Hubbell184). Similarly, high-precision modern microcalorimeters are commercially available, as are electronically controlled, temperature-regulated cells for optical spectroscopic equipment. The range of temperature–pressure studies of biological macromolecules that are possible is broad.

18.4.2 Extreme Cellular Biophysics

In the deep-sea bacterium Photobacterium profundum (Reference Campanaro, De Pascale, Telatin, Schiavon, Bartlett and Valle145), pressure affected the expression of many genes that code for proteins implicated in nutrient transport, such as outer membrane proteins (Omps). In the yeast Saccharomyces cerevisiae (Reference Iwahashi, Odani, Ishidou and Kitagawa185), pressure affected the expression of heat-shock and metabolic proteins. Upregulation of heat-shock and cold-shock protein expression in E. coli in response to high pressure has also been reported (Reference Welch, Farewell, Neidhardt and Bartlett186). It has also been shown that pressure shock of around 1000 bar leads to the filamentation of E. coli (Reference Aertsen, Van Houdt, Vanoirbeek and Michiels187), and 40 MPa has the same effect on piezophilic Desulfovibrio indonesiensis (Reference Fichtel, Logemann, Fichtel, Rulkotter, Cypionka and Engelen188), although there are likely multiple mechanisms by which this occurs. Pressure may lead to the dissociation of FtsZ, a tubulin-type GTPase involved in forming the bacterial septum for cell division (Reference Ishii, Sato, Wachi, Nagai and Kato189). However, certain strains of E. coli bear a pressure-activated Type IV restriction endonuclease, Mrr, which leads to a pressure-dependent SOS response and subsequent filamentation (Reference Aertsen and Michiels190,Reference Aertsen and Michiels191). The molecular mechanism of the pressure-induced SOS response was shown to be due to pressure-induced dissociation of the inactive Mrr tetramer to an active Mrr dimer that cleaves cryptic sites on the E. coli chromosome (Figure 18.8).

Figure 18.8 Average fluorescence intensity images of GFP-Mrr expressed from an aranbinose-inducible promoter (P_BAD) at the natural chromosomal locus in E. coli MG1655. (Left) Cells prior to the application of pressure. Full scale is 0–1.48 photon counts per 40 µs. (Right) After 10 minutes at 1 kbar and release of pressure. Full scale is 0.5–6.7 photon counts per 40 µs. Both images are 20 × 20 µm.

Results are similar to those published in (Reference Bourges, Torres Montaguth, Ghosh, Tadesse, Declerck and Aertsen192).

Although genetics, genomics, and transcriptomics can provide an overview of the putative mechanisms of adaptation to life under extreme pressures, these studies provide little biophysical insight. The study of extreme conditions on living cells remains a daunting technological challenge and requires the implementation of high-pressure quantitative microscopy approaches. A few high-pressure microscope chambers have been developed, although they have not been widely used. In the 1970s, Salmon and coworkers developed a phase contrast microscope that could withstand about 800 bar pressure (Reference Salmon and Ellis193,Reference Crenshaw and Salmon194). Müller and Gratton pioneered the use of capillary tubing for high-pressure microscopy (Reference Müller and Gratton195) that can withstand pressures up to 6000 bar. However, it has never been applied to live cell imaging. Quantitative analysis of pressure effects on bacterial mobility and flagellar rotation speed were accomplished using a recently designed high-pressure microscopy chamber (Reference Nishiyama and Kojima196). Unfortunately, owing to the thick windows of this cell, it is not suited for the high-magnification objectives required for advanced quantitative microscopy. This limitation is also the case for two other reported high-pressure microscope chamber designs (Reference Koo and Czeslik197,Reference Frey, Hartmann, Herrmann, Meyer-Pittroff, Sommer and Bluemelhuber198). Another hurdle will be the genetic manipulation of extremophile organisms in order to insert fluorescent proteins or other tags into the natural loci of genes of interest.

As in the case of high-pressure molecular biophysics, many unknowns exist regarding the molecular strategies used by cells to adapt to high-pressure or to other extreme conditions. There may be common trends (e.g. dependence on osmolytes) among different types of extremophiles. It is possible that the mechanical properties of high-pressure organisms may be different from those of their mesophilic counterparts or of hyperthermophiles, especially in their membranes and signal transduction pathways. Extreme conditions may affect cell state transitions, growth, differentiation, and development in extremophiles, or even the appearance of multicellularity. Changing geochemical conditions on Earth may have affected cellular phenotypes and the evolution of biological macromolecules.