Calibrating Bayesian Decoders of Neural Spiking Activity.

Accurately decoding external variables from observations of neural activity is a major challenge in systems neuroscience. Bayesian decoders, which provide probabilistic estimates, are some of the most widely used. Here we show how, in many common settings, the probabilistic predictions made by traditional Bayesian decoders are overconfident. That is, the estimates for the decoded stimulus or movement variables are more certain than they should be. We then show how Bayesian decoding with latent variables, taking account of low-dimensional shared variability in the observations, can improve calibration, although additional correction for overconfidence is still needed. Using data from males, we examine (1) decoding the direction of grating stimuli from spike recordings in the primary visual cortex in monkeys, (2) decoding movement direction from recordings in the primary motor cortex in monkeys, (3) decoding natural images from multiregion recordings in mice, and (4) decoding position from hippocampal recordings in rats. For each setting, we characterize the overconfidence, and we describe a possible method to correct miscalibration post hoc. Properly calibrated Bayesian decoders may alter theoretical results on probabilistic population coding and lead to brain-machine interfaces that more accurately reflect confidence levels when identifying external variables.

A metabolic map and artificial intelligence-aided identification of nasopharyngeal carcinoma via a single-cell Raman platform.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a complex cancer influenced by various factors. This study explores the use of single-cell Raman spectroscopy as a potential diagnostic tool for investigating biomolecular changes associated with NPC carcinogenesis. METHODS: Seven NPC cell lines, one immortalised nasopharyngeal epithelial cell line, six nasopharyngeal mucosa tissues and seven NPC tissue samples were analysed by performing confocal Raman spectroscopic measurements and imaging. The single-cell Raman spectral dataset was used to quantify relevant biomolecules and build machine learning classification models. Metabolomic profiles were investigated using ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). RESULTS: By generating a metabolic map of seven NPC cell lines, we identified an interplay of altered metabolic processes involving nucleic acids, amino acids, lipids and sugars. The results from spatially resolved Raman maps and UPLC-MS/MS metabolomics were consistent, revealing an increase of unsaturated fatty acids in cancer cells, particularly in highly metastatic 5-8F and poorly differentiated CNE2 cells. The classification model achieved a nearly perfect classification when identifying NPC and non-NPC cells with an ROC-AUC of 0.99 and a value of 0.97 when identifying 13 tissue samples. CONCLUSION: This study unveils a complex interplay of metabolic network and highlights the potential roles of unsaturated fatty acids in NPC progression and metastasis. This renders further research to provide deeper insights into NPC pathogenesis, identify new metabolic targets and improve the efficacy of targeted therapies in NPC. Artificial intelligence-aided analysis of single-cell Raman spectra has achieved high accuracies in the classification of both cancer cells and patient tissues, paving the way for a simple, less invasive and accurate diagnostic test.

Semi-rational design of nitroarene dioxygenase for catalytic ability toward 2,4-dichloronitrobenzene.

Rieske non-heme dioxygenase family enzymes play an important role in the aerobic biodegradation of nitroaromatic pollutants, but no active dioxygenases are available in nature for initial reactions in the degradation of many refractory pollutants like 2,4-dichloronitrobenzene (24DCNB). Here, we report the engineering of hotspots in 2,3-dichloronitrobenzene dioxygenase from Diaphorobacter sp. strain JS3051, achieved through molecular dynamic simulation analysis and site-directed mutagenesis, with the aim of enhancing its catalytic activity toward 24DCNB. The computationally predicted activity scores were largely consistent with the detected activities in wet experiments. Among them, the two most beneficial mutations (E204M and M248I) were obtained, and the combined mutant reached up to a 62-fold increase in activity toward 24DCNB, generating a single product, 3,5-dichlorocatechol, which is a naturally occurring compound. In silico analysis confirmed that residue 204 affected the substrate preference for meta-substituted nitroarenes, while residue 248 may influence substrate preference by interaction with residue 295. Overall, this study provides a framework for manipulating nitroarene dioxygenases using computational methods to address various nitroarene contamination problems.IMPORTANCEAs a result of human activities, various nitroaromatic pollutants continue to enter the biosphere with poor degradability, and dioxygenation is an important kickoff step to remove toxic nitro-groups and convert them into degradable products. The biodegradation of many nitroarenes has been reported over the decades; however, many others still lack corresponding enzymes to initiate their degradation. Although rieske non-heme dioxygenase family enzymes play extraordinarily important roles in the aerobic biodegradation of various nitroaromatic pollutants, prediction of their substrate specificity is difficult. This work greatly improved the catalytic activity of dioxygenase against 2,4-dichloronitrobenzene by computer-aided semi-rational design, paving a new way for the evolution strategy of nitroarene dioxygenase. This study highlights the potential for using enzyme structure-function information with computational pre-screening methods to rapidly tailor the catalytic functions of enzymes toward poorly biodegradable contaminants.

Fast simulation for interacting four-level Rydberg atoms: electromagnetically induced transparency and Autler-Townes splitting.

Quantum sensing using Rydberg atoms is an emerging technology for precise measurement of electric fields. However, most existing computational methods are all based on a single-particle model and neglect Rydberg-Rydberg interaction between atoms. In this study, we introduce the interaction term into the conventional four-level optical Bloch equations. By incorporating fast iterations and solving for the steady-state solution efficiently, we avoid the computation of a massive 4N × 4N dimensional matrix. Additionally, we apply the Doppler frequency shift to each atom used in the calculation, eliminating the requirement for an additional Doppler iteration. These schemes allow for the calculation of the interaction between 7000 atoms around one minute. Based on the many-body model, we investigate the Rydberg-Rydberg interaction of Rydberg atoms under different atomic densities. Furthermore, we compare our results with the literature data of a three-level system and the experimental results of our own four-level system. The results demonstrate the validity of our model, with an effective error of 4.59% compared to the experimental data. Finally, we discover that the many-body model better predicts the linear range for measuring electric fields than the single-particle model, making it highly applicable in precise electric field measurements.

Wavelength division multiplexing based on the coupling effect of helical edge states in two-dimensional dielectric photonic crystals.

Photonic topological insulators with topologically protected edge states featuring one-way, robustness and backscattering-immunity possess extraordinary abilities to steer and manipulate light. In this work, we construct a topological heterostructure (TH) consisting of a domain of nontrivial pseudospin-type topological photonic crystals (PCs) sandwiched between two domains of trivial PCs based on two-dimensional all-dielectric core-shell PCs in triangle lattice. We consider three THs with different number of layers in the middle nontrivial domain (i.e., one-layer, two-layer, three-layer) and demonstrate that the projected band diagrams of the three THs host interesting topological waveguide states (TWSs) with properties of one-way, large-area, broad-bandwidth and robustness due to coupling effect of the helical edge states associated with the two domain-wall interfaces. Moreover, taking advantage of the tunable bandgap between the TWSs by the layer number of the middle domain due to the coupling effect, a topological Y-splitter with functionality of wavelength division multiplexing is explicitly demonstrated exploiting the unique feature of the dispersion curves of TWSs in the three THs. Our work not only offers a new method to realize pseudospin-polarized large-area TWSs with tunable mode-width, but also could provide new opportunities for practical applications in on-chip multifunctional (i.e., wavelength division multiplexing) photonic devices with topological protection and information processing with pseudospin-dependent transport.

High-Q metasurface signal isolator for 1.5T surface coil magnetic resonance imaging on the go.

The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface decoupling isolator fueled by topological LC loops for 1.5T surface coil MRI system, increasing the magnetic field up to fivefold at 63.8 MHz. We have employed a polarization conversion mechanism to effectively eliminate the coupling between the MRI metamaterial and the radio frequency (RF) surface transmitter-receiver coils. Furthermore, a high-Q metasurface isolator was achieved by taking advantage of bound states in the continuum (BIC) for extremely high-resolution MRI and spectroscopy. An equivalent physical model of the miniaturized metasurface design was put forward through LC circuit analysis. This study opens up a promising route for the easy-to-use and portable surface coil MRI scanners.

Construction and validation of risk model of EMT-related prognostic genes for kidney renal clear cell carcinoma.

BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a prevalent type of urological malignancy. The present study aimed to predict biomarkers for KIRC. METHODS: We collected transcriptomic and clinical information for KIRC from The Cancer Genome Atlas and GSE22541 cohorts. RESULTS: Unsupervised clustering of 35 epithelial-mesenchymal transformation (EMT)-related differentially expressed gene profiles divided samples into two clusters with distinct immune characteristics. Six genes (IL20RB, DDC, ANKRD36BP2, F2RL1, TEK, and AMN) were found to construct a prognostic risk model using multivariate Cox regression analysis. Kaplan-Meier analysis suggested the better prognosis of the KIRC patients in the low-risk group than that in the high-risk group. Immune infiltration analyses was conducted using xCell and single-sample gene set enrichment analysis, indicating that the risk score was associated with the immune microenvironment of the KIRC. Prognostic marker gene-targeted medications with high drug sensitivity were predicted in KIRC patients. CONCLUSIONS: In summary, the present study identified IL20RB, DDC, ANKRD36BP2, F2RL1, TEK, and AMN as prognostic biomarkers, providing insight into immunotherapy and gene-targeted drugs of KIRC.

Measurement sensitivity analysis and on-orbit calibration of systematic errors for a narrow field-of-view camera.

Narrow field-of-view (FOV) cameras enable long-range observations and have been often used in deep space exploration missions. To solve the problem of systematic error calibration for a narrow FOV camera, the sensitivity of the camera systematic errors to the angle between the stars is analyzed theoretically, based on a measurement system for observing the angle between stars. In addition, the systematic errors for a narrow FOV camera are classified into "Non-attitude Errors" and "Attitude Errors". Furthermore, the on-orbit calibration methods for the two types of errors are researched. Simulations show that the proposed method is more effective in the on-orbit calibration of systematic errors for a narrow FOV camera than the traditional calibration methods.

The effectiveness of an extra-curricular lecture for STI prevention and sexual education.

While the incidence of infections with the human immunodeficiency virus largely remained unchanged in Germany, an increase of other sexually transmitted infections (STIs) was observed. The aim was to analyse the effectiveness of our sexual education lecture for students in improving the awareness, knowledge and prevention of STIs. We conducted a cross-sectional survey after students had attended our extra-curricular lecture at the Department of Dermatology of the Ludwig-Maximilians-University of Munich, Germany (LMU). We compared the data with a previously performed study in which the same survey was carried out before the lecture had started. A total of 5866 questionnaires were included in the analysis. After attending the lecture significantly more students were aware of STIs (syphilis: 36.8% (before) vs. 63.5% (after); chlamydia: 30.5% vs. 49.3%; gonorrhoea: 22.4% vs. 38.2%; human papillomaviruses (HPV): 17.7% vs. 30.2%), the transmission pathways of STIs (oral: 36.6% vs. 82.6%; vaginal: 81.8% vs. 97.3%; anal: 42.8% vs. 94.0%; penile: 68.7% vs. 92.1%), knew that the HPV vaccination is directed against a virus (36.8% vs. 56.9%) and were interested in receiving a vaccination (57.7% vs. 78.8%). This study demonstrates the positive educative effects of our lecture for awareness and improved knowledge of STIs. To satisfy the need for a comprehensive sexual education, a combination of school and health facility-based programmes should be implemented as one single lecture cannot convey the entire information about STIs.

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons.

Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.

Chromosome-free bacterial cells are safe and programmable platforms for synthetic biology.

A type of chromosome-free cell called SimCells (simple cells) has been generated from Escherichia coli, Pseudomonas putida, and Ralstonia eutropha. The removal of the native chromosomes of these bacteria was achieved by double-stranded breaks made by heterologous I-CeuI endonuclease and the degradation activity of endogenous nucleases. We have shown that the cellular machinery remained functional in these chromosome-free SimCells and was able to process various genetic circuits. This includes the glycolysis pathway (composed of 10 genes) and inducible genetic circuits. It was found that the glycolysis pathway significantly extended longevity of SimCells due to its ability to regenerate ATP and NADH/NADPH. The SimCells were able to continuously express synthetic genetic circuits for 10 d after chromosome removal. As a proof of principle, we demonstrated that SimCells can be used as a safe agent (as they cannot replicate) for bacterial therapy. SimCells were used to synthesize catechol (a potent anticancer drug) from salicylic acid to inhibit lung, brain, and soft-tissue cancer cells. SimCells represent a simplified synthetic biology chassis that can be programmed to manufacture and deliver products safely without interference from the host genome.

ICTV Virus Taxonomy Profile: Sedoreoviridae 2022.

Sedoreoviridae is a large family of icosahedral viruses that are usually regarded as non-enveloped with segmented (10-12 linear segments) dsRNA genomes of 18-26 kbp. Sedoreovirids have a broad host range, infecting mammals, birds, crustaceans, arthropods, algae and plants. Some of them have important pathogenic potential for humans (e.g. rotavirus A), livestock (e.g. bluetongue virus) and plants (e.g. rice dwarf virus). This is a summary of the ICTV Report on the family Sedoreoviridae, which is available at ictv.global/report/sedoreoviridae.

Isolation and Culture of Single Microbial Cells by Laser Ejection Sorting Technology.

Single-cell isolation and cultivation play an important role in studying physiology, gene expression, and functions of microorganisms. A series of single-cell isolation technologies have been developed, among which single-cell ejection technology is one of the most promising. Single-cell ejection technology has applied laser-induced forward transfer (LIFT) techniques to isolate bacteria, but the viability (or recovery rate) of cells after sorting has not been clarified in current research. In this work, to keep the cells alive as long as possible, we propose a three-layer LIFT system (top layer, 25-nm aluminum film; second layer, 3 µm agar media; third layer, liquid containing bacteria) for the isolation and cultivation of single Gram-negative (Escherichia coli), Gram-positive (Lactobacillus rhamnosus GG [LGG]), and eukaryotic (Saccharomyces cerevisiae) microorganisms. The experiment results showed that the average survival rates for ejected pure single cells were 63% for Saccharomyces cerevisiae, 22% for E. coli DH5α, and 74% for LGG. In addition, we successfully isolated and cultured the green fluorescent protein (GFP)-expressing E. coli JM109 from a mixture containing complex communities of soil bacteria by fluorescence signal. The average survival rate of E. coli JM109 was demonstrated to be 25.3%. In this study, the isolated and cultured single colonies were further confirmed by colony PCR and sequencing. Such precise sorting and cultivation techniques of live single microbial cells could be coupled with other microscopic approaches to isolate single microorganisms with specific functions, revealing their roles in the natural community. IMPORTANCE We developed a laser-induced forward transfer (LIFT) technology to accurately isolate single live microbial cells. The cultivation recovery rates of the ejected single cells were 63% for Saccharomyces cerevisiae, 22% for E. coli DH5α, and 74% for Lactobacillus rhamnosus GG (LGG). With coupled LIFT with a fluorescence microscope, we demonstrated that single cells of GFP-expressing E. coli JM109 were sorted according to fluorescence signal from a complex community of soil bacteria and subsequently cultured with 25% cultivation recovery rate. This single-cell live sorting technology could isolate single microbes with specific functions, revealing their roles in the natural community.

Accurate optical optimization of light-emitting diodes with consideration of coupling between Purcell factor and transmittance coefficient.

The calculation method for light emission efficiency splits external quantum efficiency (EQE) into internal quantum efficiency (IQE) and light extraction efficiency (LEE) independently. Consequently, the IQE connected to Purcell factor and the LEE are calculated separately. This traditional method ignores the interplays between the Purcell factor and transmittance coefficient in spectral domain, which all strongly depend on emitting directions. In this work, we propose a new figure of merit to describe the light emission process accurately by using the direction-dependent Purcell factor and transmittance coefficient simultaneously. We use a specific LED structure as a numerical example to illustrate the calculation method and optimization procedure.

Bound valley edge states in the continuum.

Topological valley photonics provides a unique way to manipulate the flow of light. In general, valley edge states that exhibit unidirectional propagation and are immune to defects and disorders could be realized at the interface between two valley photonic crystals with opposite valley Chern numbers. Herein, by merging the physics of valley edge states and bound states in the continuum, we propose and numerically demonstrate a novel, to the best of our knowledge, concept of edge states termed bound valley edge states in the continuum, which enjoys the topological features of valley edge states, such as, unidirectional propagation and immunity to disorders, but are formed at the interface between air and a single valley photonic crystal. Our results not only provide an effective way to reduce the size of valley photonic structures but also facilitate new applications where the proposed concept of bound valley edge states in the continuum could be exploited for optical sensing and unidirectional waveguiding.

SIRT3 (Sirtuin-3) Prevents Ang II (Angiotensin II)-Induced Macrophage Metabolic Switch Improving Perivascular Adipose Tissue Function.

OBJECTIVE: Infiltrated macrophages actively promote perivascular adipose tissue remodeling and represent a dominant population in the perivascular adipose tissue microenvironment of hypertensive mice. However, the role of macrophages in initiating metabolic inflammation remains uncertain. SIRT3 (sirtuin-3), a NAD-dependent deacetylase, is sensitive to metabolic status and mediates adaptation responses. In this study, we investigated the role of SIRT3-mediated metabolic shift in regulating NLRP3 (Nod-like receptor family pyrin domain-containing 3) inflammasome activation. Approach and Results: Here, we report that Ang II (angiotensin II) accelerates perivascular adipose tissue inflammation and fibrosis, accompanied by NLRP3 inflammasome activation and IL (interleukin)-1ß secretion in myeloid SIRT3 knockout (SIRT3-/-) mice. This effect is associated with adipose tissue mitochondrial dysfunction. In vitro studies indicate that the deletion of SIRT3 in bone marrow-derived macrophages induces IL-1ß production by shifting the metabolic phenotype from oxidative phosphorylation to glycolysis. Mechanistically, SIRT3 deacetylates and activates PDHA1 (pyruvate dehydrogenase E1 alpha) at lysine 83, and the loss of SIRT3 leads to PDH activity decrease and lactate accumulation. Knocking down LDHA (lactate dehydrogenase A) or using carnosine, a buffer against lactic acid, attenuates IL-1ß secretion. Furthermore, the blockade of IL-1ß from macrophages into brown adipocytes restores thermogenic markers and mitochondrial oxygen consumption. Moreover, NLRP3 knockout (NLRP3-/-) mice exhibited reduced IL-1ß production while rescuing the mitochondrial function of brown adipocytes and alleviating perivascular adipose tissue fibrosis. CONCLUSIONS: SIRT3 represents a potential therapeutic target to attenuate NLRP3-related inflammation. Pharmacological targeting of glycolytic metabolism may represent an effective therapeutic approach.

Integrated Terahertz Generator-Manipulators Using Epsilon-near-Zero-Hybrid Nonlinear Metasurfaces.

In terahertz (THz) technologies, generation and manipulation of THz waves are two key processes usually implemented by different device modules. Integrating THz generation and manipulation into a single compact device will advance the applications of THz technologies in various fields. Here, we demonstrate a hybrid nonlinear plasmonic metasurface incorporating an epsilon-near-zero (ENZ) indium tin oxide (ITO) layer to seamlessly combine efficient generation and manipulation of THz waves across a wide frequency band. The coupling between the plasmonic resonance of the metasurface and the ENZ mode of the ITO thin film enhances the THz conversion efficiency by more than 4 orders of magnitude. Meanwhile, such a hybrid device is capable of shaping the polarization and wavefront of the emitted THz beam via the engineered nonlinear Pancharatnam-Berry (PB) phases of the plasmonic meta-atoms. The presented hybrid nonlinear metasurface opens a new avenue toward miniaturized integrated THz devices and systems with advanced functionalities.

Understanding and mathematical modelling of cellular resource allocation in microorganisms: a comparative synthesis.

BACKGROUND: The rising consensus that the cell can dynamically allocate its resources provides an interesting angle for discovering the governing principles of cell growth and metabolism. Extensive efforts have been made in the past decade to elucidate the relationship between resource allocation and phenotypic patterns of microorganisms. Despite these exciting developments, there is still a lack of explicit comparison between potentially competing propositions and a lack of synthesis of inter-related proposals and findings. RESULTS: In this work, we have reviewed resource allocation-derived principles, hypotheses and mathematical models to recapitulate important achievements in this area. In particular, the emergence of resource allocation phenomena is deciphered by the putative tug of war between the cellular objectives, demands and the supply capability. Competing hypotheses for explaining the most-studied phenomenon arising from resource allocation, i.e. the overflow metabolism, have been re-examined towards uncovering the potential physiological root cause. The possible link between proteome fractions and the partition of the ribosomal machinery has been analysed through mathematical derivations. Finally, open questions are highlighted and an outlook on the practical applications is provided. It is the authors' intention that this review contributes to a clearer understanding of the role of resource allocation in resolving bacterial growth strategies, one of the central questions in microbiology. CONCLUSIONS: We have shown the importance of resource allocation in understanding various aspects of cellular systems. Several important questions such as the physiological root cause of overflow metabolism and the correct interpretation of 'protein costs' are shown to remain open. As the understanding of the mechanisms and utility of resource application in cellular systems further develops, we anticipate that mathematical modelling tools incorporating resource allocation will facilitate the circuit-host design in synthetic biology.

Regulation and Characterization of Mutants of fixABCX in Rhizobium leguminosarum.

Symbiosis between Rhizobium leguminosarum and Pisum sativum requires tight control of redox balance in order to maintain respiration under the microaerobic conditions required for nitrogenase while still producing the eight electrons and sixteen molecules of ATP needed for nitrogen fixation. FixABCX, a cluster of electron transfer flavoproteins essential for nitrogen fixation, is encoded on the Sym plasmid (pRL10), immediately upstream of nifA, which encodes the general transcriptional regulator of nitrogen fixation. There is a symbiotically regulated NifA-dependent promoter upstream of fixA (PnifA1), as well as an additional basal constitutive promoter driving background expression of nifA (PnifA2). These were confirmed by 5'-end mapping of transcription start sites using differential RNA-seq. Complementation of polar fixAB and fixX mutants (Fix- strains) confirmed expression of nifA from PnifA1 in symbiosis. Electron microscopy combined with single-cell Raman microspectroscopy characterization of fixAB mutants revealed previously unknown heterogeneity in bacteroid morphology within a single nodule. Two morphotypes of mutant fixAB bacteroids were observed. One was larger than wild-type bacteroids and contained high levels of polyhydroxy-3-butyrate, a complex energy/reductant storage product. A second bacteroid phenotype was morphologically and compositionally different and resembled wild-type infection thread cells. From these two characteristic fixAB mutant bacteroid morphotypes, inferences can be drawn on the metabolism of wild-type nitrogen-fixing bacteroids.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

From macro to micro: a combined bioluminescence-fluorescence approach to monitor bacterial localization.

Bacterial bioluminescence is widely used to study the spatiotemporal dynamics of bacterial populations and gene expression in vivo at a population level but cannot easily be used to study bacterial activity at the level of individual cells. In this study, we describe the development of a new library of mini-Tn7-lux and lux::eyfp reporter constructs that provide a wide range of lux expression levels, and which combine the advantages of both bacterial bioluminescence and fluorescent proteins to bridge the gap between macro- and micro-scale imaging techniques. We demonstrate that a dual bioluminescence-fluorescence approach using the lux operon and eYFP can be used to monitor bacterial movement in plants both macro- and microscopically and demonstrate that Pseudomonas syringae pv phaseolicola can colonize the leaf vascular system and systemically infect leaves of common bean (Phaseolus vulgaris). We also show that bacterial bioluminescence can be used to study the impact of plant immune responses on bacterial multiplication, viability and spread within plant tissues. The constructs and approach described in this study can be used to study the spatiotemporal dynamics of bacterial colonization and to link population dynamics and cellular interactions in a wide range of biological contexts.