Real-time bacterial microcolony counting using on-chip microscopy

Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging

In assessing food microbial safety, the presence of Escherichia coli is a critical indicator of fecal contamination. However, conventional detection methods require the isolation of bacterial macrocolonies for biochemical or genetic characterization, which takes a few days and is labor-intensive. In this study, we show that the real-time object detection and classification algorithm You Only Look Once version 4 (YOLOv4) can accurately identify the presence of E. coli at the microcolony stage after a 3-h cultivation. Integrating with phase-contrast microscopic imaging, YOLOv4 discriminated E. coli from seven other common foodborne bacterial species with an average precision of 94%. This approach also enabled the rapid quantification of E. coli concentrations over 3 orders of magnitude with an R² of 0.995. For romaine lettuce spiked with E. coli (10 to 10³ CFU/g), the trained YOLOv4 detector had a false-negative rate of less than 10%. This approach accelerates analysis and avoids manual result determination, which has the potential to be applied as a rapid and user-friendly bacterial sensing approach in food industries. IMPORTANCE A simple, cost-effective, and rapid method is desired to identify potential pathogen contamination in food products and thus prevent foodborne illnesses and outbreaks. This study combined artificial intelligence (AI) and optical imaging to detect bacteria at the microcolony stage within 3 h of inoculation. This approach eliminates the need for time-consuming culture-based colony isolation and resource-intensive molecular approaches for bacterial identification. The approach developed in this study is broadly applicable for the identification of diverse bacterial species. In addition, this approach can be implemented in resource-limited areas, as it does not require expensive instruments and significantly trained human resources. This AI-assisted detection not only achieves high accuracy in bacterial classification but also provides the potential for automated bacterial detection, reducing labor workloads in food industries, environmental monitoring, and clinical settings.

Experimental validation of stability and applicability of Start Growth Time method for high-throughput bacterial ecotoxicity assessment

Ecotoxicity assessments based on bacteria as model organisms are widely used for routine toxicity screening because it has the advantages of time-saving, high sensitivity, cost-effectiveness, and less ethical responsibility. Determination of ecotoxicity effect via bacterial growth can avoid the restriction of model bacteria selection and unique equipment requirements, but traditional viable cell count methods are relatively labor- and time-intensive. The Start Growth Time method (SGT) is a high-throughput and time-conserving method to determine the amount of viable bacterial cells. However, its usability and stability for ecotoxicity assessment are rarely studied. This study confirmed its applicability in terms of bacterial types (gram-positive and gram-negative), growth phases (middle exponential and early stationary phases), and simultaneous existence of dead cells (adjustment by flow cytometry). Our results verified that the stability of establishing SGT correlation is independent of the bacterial type and dead-cell portion. Moreover, we only observed the effect of growth phases on the slope value of established SGT correlation in Shewanella oneidensis, which suggests that preparing inoculum for the SGT method should be consistent in keeping its stability. Our results also elucidate that the SGT values and the live cell percentages meet the non-linear exponential correlation with high correlation coefficients from 0.97 to 0.99 for all the examined bacteria. The non-linear exponential correlation facilitates the application of the SGT method in the ecotoxicity assessment. Finally, applying the exponential SGT correlation to evaluate the ecotoxicity effect of copper ions on E. coli was experimentally validated. The SGT-based method would require about 6 to 7 h to finish the assessment and obtain an estimated EC₅₀ at 2.27 ± 0.04 mM. This study demonstrates that the exponential SGT correlation can be a high-throughput, time-conversing, and wide-applicable method for bacterial ecotoxicity assessment.

Diagnosing ventilator-associated pneumonia (VAP) in UK NHS ICUs: the perceived value and role of a novel optical technology

BACKGROUND

Diagnosing ventilator-associated pneumonia (VAP) in an intensive care unit (ICU) is a complex process. Our aim was to collect, evaluate and represent the information relating to current clinical practice for the diagnosis of VAP in UK NHS ICUs, and to explore the potential value and role of a novel diagnostic for VAP, which uses optical molecular alveoscopy to visualise the alveolar space.

METHODS

Qualitative study performing semi-structured interviews with clinical experts. Interviews were recorded, transcribed, and thematically analysed. A flow diagram of the VAP patient pathway was elicited and validated with the expert interviewees. Fourteen clinicians were interviewed from a range of UK NHS hospitals: 12 ICU consultants, 1 professor of respiratory medicine and 1 professor of critical care.

RESULTS

Five themes were identified, relating to [1] current practice for the diagnosis of VAP, [2] current clinical need in VAP diagnostics, [3] the potential value and role of the technology, [4] the barriers to adoption and [5] the evidence requirements for the technology, to help facilitate a successful adoption. These themes indicated that diagnosis of VAP is extremely difficult, as is the decision to stop antibiotic treatment. The analysis revealed that there is a clinical need for a diagnostic that provides an accurate and timely diagnosis of the causative pathogen, without the long delays associated with return of culture results, and which is not dangerous to the patient. It was determined that the technology would satisfy important aspects of this clinical need for diagnosing VAP (and pneumonia, more generally), but would require further evidence on safety and efficacy in the patient population to facilitate adoption.

CONCLUSIONS

Care pathway analysis performed in this study was deemed accurate and representative of current practice for diagnosing VAP in a UK ICU as determined by relevant clinical experts, and explored the value and role of a novel diagnostic, which uses optical technology, and could streamline the diagnostic pathway for VAP and other pneumonias.

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

Adaptive super-resolution enabled on-chip contact microscopy

We demonstrate an adaptive super-resolution based contact imaging on a CMOS chip to achieve subcellular spatial resolution over a large field of view of ∼24 mm². By using regular LED illumination, we acquire the single lower-resolution image of the objects placed approximate to the sensor with unit magnification. For the raw contact-mode lens-free image, the pixel size of the sensor chip limits the spatial resolution. We develop a hybrid supervised-unsupervised strategy to train a super-resolution network, circumventing the missing of in-situ ground truth, effectively recovering a much higher resolution image of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area. We demonstrate the success of this approach by imaging the proliferation dynamics of cells directly cultured on the chip.

Viable but nonculturable bacteria and their resuscitation: implications for cultivating uncultured marine microorganisms

Culturing has been the cornerstone of microbiology since Robert Koch first successfully cultured bacteria in the late nineteenth century. However, even today, the majority of microorganisms in the marine environment remain uncultivated. There are various explanations for the inability to culture bacteria in the laboratory, including lack of essential nutrients, osmotic support or incubation conditions, low growth rate, development of micro-colonies, and the presence of senescent or viable but nonculturable (VBNC) cells. In the marine environment, many bacteria have been associated with dormancy, as typified by the VBNC state. VBNC refers to a state where bacteria are metabolically active, but are no longer culturable on routine growth media. It is apparently a unique survival strategy that has been adopted by many microorganisms in response to harsh environmental conditions and the bacterial cells in the VBNC state may regain culturability under favorable conditions. The resuscitation of VBNC cells may well be an important way to cultivate the otherwise uncultured microorganisms in marine environments. Many resuscitation stimuli that promote the restoration of culturability have so far been identified; these include sodium pyruvate, quorum sensing autoinducers, resuscitation-promoting factors Rpfs and YeaZ, and catalase. In this review, we focus on the issues associated with bacterial culturability, the diversity of bacteria entering the VBNC state, mechanisms of induction into the VBNC state, resuscitation factors of VBNC cells and implications of VBNC resuscitation stimuli for cultivating these otherwise uncultured microorganisms. Bringing important microorganisms into culture is still important in the era of high-throughput sequencing as their ecological functions in the marine environment can often only be known through isolation and cultivation.

Fluorescent Copolymers for Bacterial Bioimaging and Viability Detection

Novel fluorescent labels with high photostability and high biocompatibility are required for microbiological imaging and detection. Here, we present a green fluorescent polymer chain (GFPC), designed to be nontoxic and water-soluble, for multicolor bioimaging and real-time bacterial viability determination. The copolymer is synthesized using a straightforward one-pot reversible addition-fragmentation chain-transfer (RAFT) polymerization technique. We show that GFPC does not influence bacterial growth and is stable for several hours in a complex growth medium and in the presence of bacteria. GFPC allows the labeling of the bacterial cytoplasm for multicolor bacterial bioimaging applications. It can be used in combination with propidium iodide (PI) to develop a rapid and reliable protocol to distinguish and quantify, in real time, by flow cytometry, live and dead bacteria.

Photodegradable Hydrogels for Rapid Screening, Isolation, and Genetic Characterization of Bacteria with Rare Phenotypes

Screening mutant libraries (MLs) of bacteria for strains with specific phenotypes is often a slow and laborious process that requires assessment of tens of thousands of individual cell colonies after plating and culturing on solid media. In this report, we develop a three-dimensional, photodegradable hydrogel interface designed to dramatically improve the throughput of ML screening by combining high-density cell culture with precision extraction and the recovery of individual, microscale colonies for follow-up genetic and phenotypic characterization. ML populations are first added to a hydrogel precursor solution consisting of polyethylene glycol (PEG) o-nitrobenzyl diacrylate and PEG-tetrathiol macromers, where they become encapsulated into 13 μm thick hydrogel layers at a density of 90 cells/mm², enabling parallel monitoring of 2.8 × 10⁴ mutants per hydrogel. Encapsulated cells remain confined within the elastic matrix during culture, allowing one to track individual cells that grow into small, stable microcolonies (45 ± 4 μm in diameter) over the course of 72 h. Colonies with rare growth profiles can then be identified, extracted, and recovered from the hydrogel in a sequential manner and with minimal damage using a high-resolution, 365 nm patterned light source. The light pattern can be varied to release motile cells, cellular aggregates, or microcolonies encapsulated in protective PEG coatings. To access the benefits of this approach for ML screening, an Agrobacterium tumefaciens C58 transposon ML was screened for rare, resistant mutants able to grow in the presence of cell free culture media from Rhizobium rhizogenes K84, a well-known inhibitor of C58 cell growth. Subsequent genomic analysis of rare cells (9/28,000) that developed into microcolonies identified that seven of the resistant strains had mutations in the acc locus of the Ti plasmid. These observations are consistent with past research demonstrating that the disruption of this locus confers resistance to agrocin 84, an inhibitory molecule produced by K84. The high-throughput nature of the screen allows the A. tumefaciens genome (approximately 5.6 Mbps) to be screened to saturation in a single experimental trial, compared to hundreds of platings required by conventional plating approaches. As a miniaturized version of the gold-standard plating assay, this materials-based approach offers a simple, inexpensive, and highly translational screening technique that does not require microfluidic devices or complex liquid handling steps. The approach is readily adaptable to other applications that require isolation and study of rare or phenotypically pure cell populations.

Food Microstructure and Fat Content Affect Growth Morphology, Growth Kinetics, and Preferred Phase for Cell Growth of Listeria monocytogenes in Fish-Based Model Systems

Food microstructure significantly affects microbial growth dynamics, but knowledge concerning the exact influencing mechanisms at a microscopic scale is limited. The food microstructural influence on Listeria monocytogenes (green fluorescent protein strain) growth at 10°C in fish-based food model systems was investigated by confocal laser scanning microscopy. The model systems had different microstructures, i.e., liquid, xanthan (high-viscosity liquid), aqueous gel, and emulsion and gelled emulsion systems varying in fat content. Bacteria grew as single cells, small aggregates, and microcolonies of different sizes (based on colony radii [size I, 1.5 to 5.0 μm; size II, 5.0 to 10.0 μm; size III, 10.0 to 15.0 μm; and size IV, ≥15 μm]). In the liquid, small aggregates and size I microcolonies were predominantly present, while size II and III microcolonies were predominant in the xanthan and aqueous gel. Cells in the emulsions and gelled emulsions grew in the aqueous phase and on the fat-water interface. A microbial adhesion to solvent assay demonstrated limited bacterial nonpolar solvent affinities, implying that this behavior was probably not caused by cell surface hydrophobicity. In systems containing 1 and 5% fat, the largest cell volume was mainly represented by size I and II microcolonies, while at 10 and 20% fat a few size IV microcolonies comprised nearly the total cell volume. Microscopic results (concerning, e.g., growth morphology, microcolony size, intercolony distances, and the preferred phase for growth) were related to previously obtained macroscopic growth dynamics in the model systems for an L. monocytogenes strain cocktail, leading to more substantiated explanations for the influence of food microstructural aspects on lag phase duration and growth rate.IMPORTANCEListeria monocytogenes is one of the most hazardous foodborne pathogens due to the high fatality rate of the disease (i.e., listeriosis). In this study, the growth behavior of L. monocytogenes was investigated at a microscopic scale in food model systems that mimic processed fish products (e.g., fish paté and fish soup), and the results were related to macroscopic growth parameters. Many studies have previously focused on the food microstructural influence on microbial growth. The novelty of this work lies in (i) the microscopic investigation of products with a complex composition and/or structure using confocal laser scanning microscopy and (ii) the direct link to the macroscopic level. Growth behavior (i.e., concerning bacterial growth morphology and preferred phase for growth) was more complex than assumed in common macroscopic studies. Consequently, the effectiveness of industrial antimicrobial food preservation technologies (e.g., thermal processing) might be overestimated for certain products, which may have critical food safety implications.

Development of an automated wet-cyclone system for rapid, continuous and enriched bioaerosol sampling and its application to real-time detection

We present a novel bioaerosol sampling system based on a wet-cyclone for real-time and continuous monitoring of airborne microorganisms. The Automated and Real-time Bioaerosol Sampler based on Wet-cyclone (ARBSW) continuously collects bioaerosols in a liquid medium and delivers the samples to a sensing device using a wireless remote control system. Based on a high air-to-liquid-flow-rate ratio (∼ 1.4 × 10⁵) and a stable liquid thin film within a wet-cyclone, the system achieved excellent sampling performance as indicated by the high concentration and viability of bioaerosols (> 95% collection efficiency for > 0.5-μm-diameter particles, > 95% biological collection efficiency for Staphylococcus epidermidis and Micrococcus luteus). Furthermore, the continuous and real-time sampling performance of the ARBSW system under test-bed conditions and during a field test demonstrated that the ARBSW is capable of continuously monitoring bioaerosols in real time with high sensitivity. Therefore, the ARBSW shows promise for continuous real-time monitoring of bioaerosols and will facilitate the management of bioaerosol-related health and environmental issues.

Smartphone-based rapid quantification of viable bacteria by single-cell microdroplet turbidity imaging

Standard plate count (SPC) has been recognized as the golden standard for the quantification of viable bacteria. However, SPC usually takes one to several days to grow individual cells into a visible colony, which greatly hampers its application in rapid bacteria enumeration. Here we present a microdroplet turbidity imaging based digital standard plate count (dSPC) method to overcome this hurdle. Instead of cultivating on agar plates, bacteria are encapsulated in monodisperse microdroplets for single-cell cultivation. Proliferation of the encapsulated bacterial cell produced a detectable change in microdroplet turbidity, which allowed, after just a few bacterial doubling cycles (i.e., a few hours), enumeration of viable bacteria by visible-light imaging. Furthermore, a dSPC platform integrating a power-free droplet generator with smartphone-based turbidity imaging was established. As proof-of-concept demonstrations, a series of Gram-negative bacteria (Escherichia coli) and Gram-positive bacteria (Bacillus subtilis) samples were quantified via the smartphone dSPC accurately within 6 hours, representing a detection sensitivity of 100 CFU ml-1 and at least 3 times faster. In addition, Enterobacter sakazakii (E. sakazakii) in infant milk powder as a real sample was enumerated within 6 hours, in contrast to the 24 hours needed in traditional SPC. Results with high accuracy and reproducibility were achieved, with no difference in counts found between dSPC and SPC. By enabling label-free, rapid, portable and low-cost enumeration and cultivation of viable bacteria onsite, smartphone dSPC forms the basis for a temporally and geographically trackable network for surveying live microbes globally where every citizen with a cellphone can contribute anytime and anywhere.

Digital, Rapid, Accurate, and Label-Free Enumeration of Viable Microorganisms Enabled by Custom-Built On-Glass-Slide Culturing Device and Microscopic Scanning

Accurately measuring the number of viable microorganisms plays an essential role in microbiological studies. Since the conventional agar method of enumerating visible colonies is time-consuming and not accurate, efforts have been made towards overcoming these limitations by counting the invisible micro-colonies. However, none of studies on micro-colony counting was able to save significant time or provide accurate results. Herein, we developed an on-glass-slide cell culture device that enables rapid formation of micro-colonies on a 0.38 mm-thick gel film without suffering from nutrient and oxygen deprivation during bacteria culturing. Employing a phase contrast imaging setup, we achieved rapid microscopic scanning of micro-colonies within a large sample area on the thin film without the need of fluorescent staining. Using Escherichia coli (E. coli) as a demonstration, our technique was able to shorten the culturing time to within 5 h and automatically enumerate the micro-colonies from the phase contrast images. Moreover, this method delivered more accurate counts than the conventional visible colony counting methods. Due to these advantages, this imaging-based micro-colony enumeration technique provides a new platform for the quantification of viable microorganisms.

Advances in online methods for monitoring microbial growth

Understanding the characteristics of microbial growth is of great significance to many fields including in scientific research, the food industry, health care, and agriculture. Many methods have been established to characterize the process of microbial growth. Online and automated methods, in which sample transfer is avoided, are popular because they can facilitate the development of simple, safe, and effective growth monitoring. This review focuses on advances in online monitoring methods over the last decade (2008-2018). We specifically focus on optic- and electrochemistry-based techniques, either through contact measurements or contactless measurement. Strengths and weaknesses of each set of methods are described and we also speculate on forthcoming trends in the field.

G3 PhyloChip Analysis Confirms the Promise of Plant-Based Culture Media for Unlocking the Composition and Diversity of the Maize Root Microbiome and for Recovering Unculturable Candidate Divisions/Phyla

The rapid development of high-throughput techniques and expansion of bacterial databases have accelerated efforts to bring plant microbiomes into cultivation. We introduced plant-only-based culture media as a successful candidate to mimic the nutritional matrices of plant roots. We herein employed a G3 PhyloChip microarray to meticulously characterize the culture-dependent and -independent bacterial communities of the maize root compartments, the endo- and ecto-rhizospheres. An emphasis was placed on the preference of the growth of unculturable candidate divisions/phyla on plant-only-based culture media over standard culture media (nutrient agar). A total of 1,818 different operational taxonomic units (OTUs) were resolved representing 67 bacterial phyla. Plant-only-based culture media displayed particular affinity towards recovering endophytic over ectophytic rhizobacteria. This was shown by the slightly higher recovery of CFUs for endophytes on plant-only-based culture media (26%) than on standard culture media (10%) as well as the higher taxa richness and numbers of exclusive families of unculturable divisions/phyla. Out of 30 bacterial phyla (comprising >95% of the whole population), 13 were of a significantly higher incidence on plant-only-based culture media, 6 phyla of which were not-yet-cultured (Atribacteria, OP9; Dependentiae, TM6; Latescibacteria, WS3; Marinimicrobia, SAR406; Omnitrophica, OP3; BRC1). Furthermore, plant-only-based culture media significantly enriched less abundant and/or hard-to-culture bacterial phyla (Acidobacteria, Gemmatimonadetes, and Tenericutes). These results present conclusive evidence of the ability of plant-only-based culture media to bring the plant-fed in situ microbiome into the status of plant-fed in vitro cultures, and to widen the scope of cultivation of heretofore-unculturable bacterial divisions/phyla.

Colony Fingerprint-Based Discrimination of Staphylococcus species with Machine Learning Approaches

Detection and discrimination of bacteria are crucial in a wide range of industries, including clinical testing, and food and beverage production. Staphylococcus species cause various diseases, and are frequently detected in clinical specimens and food products. In particular, S. aureus is well known to be the most pathogenic species. Conventional phenotypic and genotypic methods for discrimination of Staphylococcus spp. are time-consuming and labor-intensive. To address this issue, in the present study, we applied a novel discrimination methodology called colony fingerprinting. Colony fingerprinting discriminates bacterial species based on the multivariate analysis of the images of microcolonies (referred to as colony fingerprints) with a size of up to 250 μm in diameter. The colony fingerprints were obtained via a lens-less imaging system. Profiling of the colony fingerprints of five Staphylococcus spp. (S. aureus, S. epidermidis, S. haemolyticus, S. saprophyticus, and S. simulans) revealed that the central regions of the colony fingerprints showed species-specific patterns. We developed 14 discriminative parameters, some of which highlight the features of the central regions, and analyzed them by several machine learning approaches. As a result, artificial neural network (ANN), support vector machine (SVM), and random forest (RF) showed high performance for discrimination of theses bacteria. Bacterial discrimination by colony fingerprinting can be performed within 11 h, on average, and therefore can cut discrimination time in half compared to conventional methods. Moreover, we also successfully demonstrated discrimination of S. aureus in a mixed culture with Pseudomonas aeruginosa. These results suggest that colony fingerprinting is useful for discrimination of Staphylococcus spp.

Reducing Uncertainty for Acute Febrile Illness in Resource-Limited Settings: The Current Diagnostic Landscape

AbstractDiagnosing the cause of acute febrile illness in resource-limited settings is important-to give the correct antimicrobials to patients who need them, to prevent unnecessary antimicrobial use, to detect emerging infectious diseases early, and to guide vaccine deployment. A variety of approaches are yielding more rapid and accurate tests that can detect more pathogens in a wider variety of settings. After decades of slow progress in diagnostics for acute febrile illness in resource-limited settings, a wave of converging advancements will enable clinicians in resource-limited settings to reduce uncertainty for the diagnosis of acute febrile illness.

Colony fingerprint for discrimination of microbial species based on lensless imaging of microcolonies

Detection and identification of microbial species are crucial in a wide range of industries, including production of beverages, foods, cosmetics, and pharmaceuticals. Traditionally, colony formation and its morphological analysis (e.g., size, shape, and color) with a naked eye have been employed for this purpose. However, such a conventional method is time consuming, labor intensive, and not very reproducible. To overcome these problems, we propose a novel method that detects microcolonies (diameter 10–500 μm) using a lensless imaging system. When comparing colony images of five microorganisms from different genera (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans), the images showed obvious different features. Being closely related species, St. aureus and St. epidermidis resembled each other, but the imaging analysis could extract substantial information (colony fingerprints) including the morphological and physiological features, and linear discriminant analysis of the colony fingerprints distinguished these two species with 100% of accuracy. Because this system may offer many advantages such as high-throughput testing, lower costs, more compact equipment, and ease of automation, it holds promise for microbial detection and identification in various academic and industrial areas.

Impact of saccharides on the drying kinetics of agarose gels measured by in-situ interferometry

Agarose gels are viscoelastic soft solids that display a porous microstructure filled with water at 90% w/w or more. Despite an extensive use in food industry and microbiology, little is known about the drying kinetics of such squishy solids, which suffers from a lack of time-resolved local measurements. Moreover, only scattered empirical observations are available on the role of the gel composition on the drying kinetics. Here we study by in-situ interferometry the drying of agarose gels of various compositions cast in Petri dishes. The gel thinning is associated with the displacement of interference fringes that are analyzed using an efficient spatiotemporal filtering method, which allows us to assess local thinning rates as low as 10 nm/s with high accuracy. The gel thinning rate measured at the center of the dish appears as a robust observable to quantify the role of additives on the gel drying kinetics and compare the drying speed of agarose gels loaded with various non-gelling saccharides of increasing molecular weights. Our work shows that saccharides systematically decrease the agarose gel thinning rate up to a factor two, and exemplifies interferometry as a powerful tool to quantify the impact of additives on the drying kinetics of polymer gels.

General calibration of microbial growth in microplate readers

Optical density (OD) measurements of microbial growth are one of the most common techniques used in microbiology, with applications ranging from studies of antibiotic efficacy to investigations of growth under different nutritional or stress environments, to characterization of different mutant strains, including those harbouring synthetic circuits. OD measurements are performed under the assumption that the OD value obtained is proportional to the cell number, i.e. the concentration of the sample. However, the assumption holds true in a limited range of conditions, and calibration techniques that determine that range are currently missing. Here we present a set of calibration procedures and considerations that are necessary to successfully estimate the cell concentration from OD measurements.