Catechol 2,3-dioxygenase-assisted cleavage of aromatics by “anaerobic” termite gut spirochetes and genomic evidence of a complete meta-pathway

The termite hindgut microbial ecosystem functions like a miniature lignocellulose-metabolizing natural bioreactor, has significant implications to nutrient cycling in the terrestrial environment, and represents an array of microbial metabolic diversity. Deciphering the intricacies of this microbial community to obtain as complete a picture as possible of how it functions as a whole, requires a combination of various traditional and cutting-edge bioinformatic, molecular, physiological, and culturing approaches. Isolates from this ecosystem, including Treponema primitia str. ZAS-1 and ZAS-2 as well as T. azotonutricium str. ZAS-9, have been significant resources for better understanding the termite system. While not all functions predicted by the genomes of these three isolates are demonstrated in vitro, these isolates do have the capacity for several metabolisms unique to spirochetes and critical to the termite system’s reliance upon lignocellulose. In this thesis, work culturing, enriching for, and isolating diverse microorganisms from the termite hindgut is discussed. Additionally, strategies of members of the termite hindgut microbial community to defend against O₂-stress and to generate acetate, the “biofuel” of the termite system, are proposed. In particular, catechol 2,3-dioxygenase and other meta-cleavage catabolic pathway genes are described in the “anaerobic” termite hindgut spirochetes T. primitia str. ZAS-1 and ZAS-2, and the first evidence for aromatic ring cleavage in the phylum (division) Spirochetes is also presented. These results suggest that the potential for O₂-dependent, yet nonrespiratory, metabolisms of plant-derived aromatics should be re-evaluated in termite hindgut communities. Potential future work is also illustrated.

Chelation-enforced metal-arene interactions : insights into substrate binding and catalysis by late transition metal complexes

Understanding and catalyzing chemical reactions requiring multiple electron transfers is an endeavor relevant to many outstanding challenges in the field of chemistry. To study multi-electron reactions, a terphenyl diphosphine framework was designed to support one or more metals in multiple redox states via stabilizing interactions with the central arene of the terphenyl backbone. A variety of unusual compounds and reactions and their relevance toward prominent research efforts in chemistry are the subject of this dissertation.

Chapter 2 introduces the para-terphenyl diphosphine framework and its coordination chemistry with group 10 transition metal centers. Both mononuclear and dinuclear compounds are characterized. In many cases, the metal center(s) are stabilized by the terphenyl central arene. These metal–arene interactions are characterized both statically, in the solid state, and fluxionally, in solution. As a proof-of-principle, a dinickel framework is shown to span multiple redox states, showing that multielectron chemistry can be supported by the coordinatively flexible terphenyl diphosphine.

Chapter 3 presents reactivity of the terphenyl diphosphine when bound to a metal center. Because of the dearomatizing effect of the metal center, the central arene of the ligand is susceptible to reactions that do not normally affect arenes. In particular, Ni-to-arene H-transfer and arene dihydrogenation reactions are presented. Additionally, evidence for reversibility of the Ni-to-arene H-transfer is discussed.

Chapter 4 expands beyond the chelated metal-arene interactions of the previous chapters. A dipalladium(I) terphenyl diphosphine framework is used to bind a variety of exogenous organic ligands including arenes, dienes, heteroarenes, thioethers, and anionic ligands. The compounds are structurally characterized, and many ligands exhibit unprecedented bindng modes across two metal centers. The relative binding affinities are evaluated spectroscopically, and equilibrium binding constants for the examined ligands are determined to span over 13 orders of magnitude. As an application of this framework, mild hydrogenation conditions of bound thiophene are presented.

Chapter 5 studies nickel-mediated C–O bond cleavage of aryl alkyl ethers, a transformation with emerging applications in fields such as lignin biofuels and organic methodology. Other group members have shown the mechanism of C–O bond cleavage of an aryl methyl ether incorporated into a meta-terphenyl diphosphine framework to proceed through β-H elimination of an alkoxide. First, the electronic selectivity of the model system is examined computationally and compared with catalytic systems. The lessons learned from the model system are then applied to isotopic labeling studies for catalytic aryl alkyl ether cleavage under dihydrogen. Results from selective deuteration experiments and mass spectrometry draw a clear analogy between the mechanisms of the model and catalytic systems that does not require dihydrogen for C–O bond cleavage, although dihydrogen is proposed to play a role in catalyst activation and catalytic turnover.

Appendix A presents initial efforts toward heterodinuclear complexes as models for CO dehydrogenase and Fischer Tropsch chemistry. A catechol-incorporating terphenyl diphosphine is reported, and metal complexes thereof are discussed.

Appendix B highlights some structurally characterized terphenyl diphosphine complexes that either do not thematically belong in the research chapters or proved to be difficult to reproduce. These compounds show unusual coordination modes of the terphenyl diphosphine from which other researchers may glean insights.

DNA-Mediated Charge Transport Devices for Protein Detection

Detection of biologically relevant targets, including small molecules, proteins, DNA, and RNA, is vital for fundamental research as well as clinical diagnostics. Sensors with biological elements provide a natural foundation for such devices because of the inherent recognition capabilities of biomolecules. Electrochemical DNA platforms are simple, sensitive, and do not require complex target labeling or expensive instrumentation. Sensitivity and specificity are added to DNA electrochemical platforms when the physical properties of DNA are harnessed. The inherent structure of DNA, with its stacked core of aromatic bases, enables DNA to act as a wire via DNA-mediated charge transport (DNA CT). DNA CT is not only robust over long molecular distances of at least 34 nm, but is also especially sensitive to anything that perturbs proper base stacking, including DNA mismatches, lesions, or DNA-binding proteins that distort the π-stack. Electrochemical sensors based on DNA CT have previously been used for single-nucleotide polymorphism detection, hybridization assays, and DNA-binding protein detection. Here, improvements to (i) the structure of DNA monolayers and (ii) the signal amplification with DNA CT platforms for improved sensitivity and detection are described.

First, improvements to the control over DNA monolayer formation are reported through the incorporation of copper-free click chemistry into DNA monolayer assembly. As opposed to conventional film formation involving the self-assembly of thiolated DNA, copper-free click chemistry enables DNA to be tethered to a pre-formed mixed alkylthiol monolayer. The total amount of DNA in the final film is directly related to the amount of azide in the underlying alkylthiol monolayer. DNA monolayers formed with this technique are significantly more homogeneous and lower density, with a larger amount of individual helices exposed to the analyte solution. With these improved monolayers, significantly more sensitive detection of the transcription factor TATA binding protein (TBP) is achieved.

Using low-density DNA monolayers, two-electrode DNA arrays were designed and fabricated to enable the placement of multiple DNA sequences onto a single underlying electrode. To pattern DNA onto the primary electrode surface of these arrays, a copper precatalyst for click chemistry was electrochemically activated at the secondary electrode. The location of the secondary electrode relative to the primary electrode enabled the patterning of up to four sequences of DNA onto a single electrode surface. As opposed to conventional electrochemical readout from the primary, DNA-modified electrode, a secondary microelectrode, coupled with electrocatalytic signal amplification, enables more sensitive detection with spatial resolution on the DNA array electrode surface. Using this two-electrode platform, arrays have been formed that facilitate differentiation between well-matched and mismatched sequences, detection of transcription factors, and sequence-selective DNA hybridization, all with the incorporation of internal controls.

For effective clinical detection, the two working electrode platform was multiplexed to contain two complementary arrays, each with fifteen electrodes. This platform, coupled with low density DNA monolayers and electrocatalysis with readout from a secondary electrode, enabled even more sensitive detection from especially small volumes (4 μL per well). This multiplexed platform has enabled the simultaneous detection of two transcription factors, TBP and CopG, with surface dissociation constants comparable to their solution dissociation constants.

With the sensitivity and selectivity obtained from the multiplexed, two working electrode array, an electrochemical signal-on assay for activity of the human methyltransferase DNMT1 was incorporated. DNMT1 is the most abundant human methyltransferase, and its aberrant methylation has been linked to the development of cancer. However, current methods to monitor methyltransferase activity are either ineffective with crude samples or are impractical to develop for clinical applications due to a reliance on radioactivity. Electrochemical detection of methyltransferase activity, in contrast, circumvents these issues. The signal-on detection assay translates methylation events into electrochemical signals via a methylation-specific restriction enzyme. Using the two working electrode platform combined with this assay, DNMT1 activity from tumor and healthy adjacent tissue lysate were evaluated. Our electrochemical measurements revealed significant differences in methyltransferase activity between tumor tissue and healthy adjacent tissue.

As differential activity was observed between colorectal tumor tissue and healthy adjacent tissue, ten tumor sets were subsequently analyzed for DNMT1 activity both electrochemically and by tritium incorporation. These results were compared to expression levels of DNMT1, measured by qPCR, and total DNMT1 protein content, measured by Western blot. The only trend detected was that hyperactivity was observed in the tumor samples as compared to the healthy adjacent tissue when measured electrochemically. These advances in DNA CT-based platforms have propelled this class of sensors from the purely academic realm into the realm of clinically relevant detection.

Metastability and dynamics of stem cells: from direct observations to inference at the single cell level

Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.