Distinct growth strategies of soil bacteria as revealed by large-scale colony tracking

Our understanding of microbial ecology has been significantly furthered in recent years by advances in sequencing techniques, but comprehensive surveys of the phenotypic characteristics of environmental bacteria remain rare. Such phenotypic data are crucial for understanding the microbial strategies for growth and the diversity of microbial ecosystems. Here, we describe a high-throughput measurement of the growth of thousands of bacterial colonies using an array of flat-bed scanners coupled with automated image analysis. We used this system to investigate the growth properties of members of a microbial community from untreated soil. The system provides high-quality measurements of the number of CFU, colony growth rates, and appearance times, allowing us to directly study the distribution of these properties in mixed environmental samples. We find that soil bacteria display a wide range of growth strategies which can be grouped into several clusters that cannot be reduced to any of the classical dichotomous divisions of soil bacteria, e.g., into copiotophs and oligotrophs. We also find that, at early times, cells are most likely to form colonies when other, nearby colonies are present but not too dense. This maximization of culturability at intermediate plating densities suggests that the previously observed tendency for high density to lead to fewer colonies is partly offset by the induction of colony formation caused by interactions between microbes. These results suggest new types of growth classification of soil bacteria and potential effects of species interactions on colony growth.     

Quantitative Infrared Photoanalysis of Selected Bacteria

A technique to measure transmitted infrared radiation from minute biological systems is described. Infrared color film was exposed by radiation transmitted through bacterial colonies. The resultant photographic image was unique for each species of bacteria examined and spectral analysis of the image provided differential light emission patterns which could be quantitated. A formula for developing numerical comparisons among bacterial colonies was provided. The results of this numerical procedure gave quantitative relationships for the total infrared data from each microbial colony and made possible the differential identification of ten species of medically significant bacteria.     

COVASIAM: an Image Analysis Method That Allows Detection of Confluent Microbial Colonies and Colonies of Various Sizes for Automated Counting

In this work we introduce the confluent and various sizes image analysis method (COVASIAM), an automated colony count technique that uses digital imaging technology for detection and separation of confluent microbial colonies and colonies of various sizes growing on petri dishes. The proposed method takes advantage of the optical properties of the surfaces of most microbial colonies. Colonies in the petri dish are epi-illuminated in order to direct the reflection of concentrated light coming from a halogen lamp towards an image-sensing device. In conjunction, a multilevel threshold algorithm is proposed for colony separation and counting. These procedures improved the quantification of colonies showing confluence or differences in size. We tested COVASIAM with a sample set of microorganisms that form colonies with contrasting physical properties: Saccharomyces cerevisiae, Aspergillus nidulans, Escherichia coli, Azotobacter vinelandii, Pseudomonas aeruginosa, and Rhizobium etli. These physical properties range from smooth to hairy, from bright to opaque, and from high to low convexities. COVASIAM estimated an average of 95.47% (ς = 8.55%) of the manually counted colonies, while an automated method based on a single-threshold segmentation procedure estimated an average of 76% (ς = 16.27) of the manually counted colonies. This method can be easily transposed to almost every image-processing analyzer since the procedures to compile it are generically standard.     

Direct identification of pure Penicillium species using image analysis

This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been established. Using a digital image it is possible to extract precise information from the surface of the fungal colony. This includes color distribution, colony dimensions and texture measurements. For fungal identification, this is normally done by visual observation that often results in a very subjective data recording. Isolates of nine different species of the genus Penicillium have been selected for the purpose. After incubation for 7 days, the fungal colonies are digitized using a very accurate digital camera. Prior to the image analysis each image is corrected for self-illumination, thereby gaining a set of directly corresponding images with respect to illumination. A Windows application has been developed to locate the position and size of up to three colonies in the digitized image. Using the estimated positions and sizes of the colonies, a number of relevant features can be extracted for further analysis. The method used to determine the position of the colonies will be covered as well as the feature selection. The texture measurements of colonies of the nine species were analyzed and a clustering of the data into the correct species was confirmed. This indicates that it is indeed possible to identify a given colony merely by macromorphological features. A classifier (in the normal distribution) based on measurements of 151 colonies incubated on yeast extract sucrose agar (YES) was used to discriminate between the species. This resulted in a correct classification rate of 100% when used on the training set and 96% using cross-validation. The same methods applied to 194 colonies incubated on Czapek yeast extract agar (CYA) resulted in a correct classification rate of 98% on the training set and 71% using cross-validation.     

The effect of sodium chloride concentration and pH on the growth of Salmonella typhimurium colonies on solid medium

The growth of Salmonella typhimurium colonies on a model food system (agar solidified culture medium) was followed. Colony radius, determined using computer image analysis (IA) techniques, and viable cell number per colony were measured as indices of colony growth, and the effect of [NaCl] (0.5–3.5% (w/v)) and pH (7.0–5.0) on colony growth at 30°C was observed; colonies were point inoculated from serial dilutions. Colony growth (between 13 and 26 h after inoculation) was linear when expressed in terms of radius, and exponential when expressed in terms of viable cell number per colony. Overall, both increasing the [NaCl] and decreasing the pH had little effect on colony growth, other than to delay the onset of linear radial growth. Initial specific growth rate (μ) ranged from 0.73 to 0.87 h⁻¹. Thin films of agar medium on microscope slides allowed the growth of microcolonies to be observed after just 4 h incubation. A greater understanding of the growth kinetics of bacterial colonies, and the effects of environment on such data, may enable better control of foodborne bacterial pathogens, and consequently an improvement in food product safety.     

Automated Count and Size Evaluation of Colonies of Bacteria Grown in a Zonal Concentration Gradient of Antimicrobial Agent

The quantitative study (counting and size and surface evaluation of bacterial colonies) of the activity of an antimicrobial agent against a microbial population growing in solid medium can be performed by an electronic image analyzer. The Zeiss Micro-Videomat allowed the detection of even slight antimicrobial effects, which would be difficult to detect by colony counting alone and would escape the manual procedures of observation. The potential of the new method of investigation was illustrated by the examination of Staphylococcus aureus inhibition zones produced by disks of penicillin G and sulfadiazine.     

Uptake of Glucose and Phosphorus by Growing Colonies of Fusarium oxysporum as Quantified by Image Analysis

Olsson, S. 1994. Uptake of glucose and phosphorus by growing colonies of Fusarium oxysporum as quantified by image analysis. Experimental Mycology 18, 33-47. The simplest of all heterogeneous environments for fungal colony growth is the petri dish with an agar medium. As the colony grows there will be a depression of nutrient concentrations under the colony caused by the uptake of nutrients by the growing colony. Image analysis methods have been developed for measuring medium concentrations of glucose and phosphorus with simultaneous biomass density determinations in agar systems. Maps of the concentrations in the agar medium under the colony and of colony biomass density were produced. A new method for weighing fungal colonies grown on agar is also presented. For Fusarium oxysporum phosphorus and glucose uptake from the medium was the same irrespective of the C/mineral ratios in the medium within the measured range of ratios. Even the concentration profiles of the nutrients under the colony were the same irrespective of nutrient ratios. Distribution of biomass density was affected by differences in glucose concentrations, being highest at the colony margin at the lower concentrations. The results indicate that the fungal colony is able to take up nutrients at the margin in excess of the local needs.     

Automated image analysis with the potential for process quality control applications in stem cell maintenance and differentiation

The translation of laboratory processes into scaled production systems suitable for manufacture is a significant challenge for cell based therapies; in particular there is a lack of analytical methods that are informative and efficient for process control. Here the potential of image analysis as one part of the solution to this issue is explored, using pluripotent stem cell colonies as a valuable and challenging exemplar. The Cell‐IQ live cell imaging platform was used to build image libraries of morphological culture attributes such as colony “edge,” “core periphery” or “core” cells. Conventional biomarkers, such as Oct3/4, Nanog, and Sox‐2, were shown to correspond to specific morphologies using immunostaining and flow cytometry techniques. Quantitative monitoring of these morphological attributes in‐process using the reference image libraries showed rapid sensitivity to changes induced by different media exchange regimes or the addition of mesoderm lineage inducing cytokine BMP4. The imaging sample size to precision relationship was defined for each morphological attribute to show that this sensitivity could be achieved with a relatively low imaging sample. Further, the morphological state of single colonies could be correlated to individual colony outcomes; smaller colonies were identified as optimum for homogenous early mesoderm differentiation, while larger colonies maintained a morphologically pluripotent core. Finally, we show the potential of the same image libraries to assess cell number in culture with accuracy comparable to sacrificial digestion and counting. The data supports a potentially powerful role for quantitative image analysis in the setting of in‐process specifications, and also for screening the effects of process actions during development, which is highly complementary to current analysis in optimization and manufacture. © 2015 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 32:215–223, 2016     

Microbial communities associated with skeletal tumors on Porites compressa

Coral tumors are atypical skeletal forms found on coral reefs worldwide. Here we present an analysis of the microbial communities associated with skeletal tumors on the coral Porites compressa. Microbial growth rates on both healthy and tumorous P. compressa were decoupled from the surrounding water column. Microbial communities associated with tumorous colonies had a significantly faster growth rate than those associated with healthy P. compressa. The microbial community associated with the tumors contained more culturable Vibrio spp. and could utilize more carbon sources than the microbes associated with healthy colonies. Presence of tumors affected the composition and dynamics of the microbial population associated with the entire colony.     

Application of robotics and image processing to automated colony picking and arraying.

We describe a system that applies image processing and robotic techniques to automatically pick individual colonies from square petri dishes and array them in 96-well microtiter plates. Digital images of the colony distribution in the dishes are acquired using a video camera and frame buffer. Commercial image processing software is used to identify individual colonies and determine their locations. A Hewlett-Packard Microassay System robot reads the resulting coordinate file for each dish, picks cells from each identified colony and transfers the cells into a microtiter plate well. A disposable pipet tip is used as the sterile implement for colony picking. Custom holders position the dishes accurately and provide common coordinate systems for imaging and picking. The system is calibrated to account for the depth of agar in the dishes. The robot can process up to 10 dishes and 20 plates (1920 colonies) in a single run. It has successfully arrayed a cosmid library of the S. pombe genome consisting of approximately 6000 colonies in 30 petri dishes in about 40 hours of robot time. Future enhancements to the system are discussed.     

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Growth dynamics are fundamental characteristics of microorganisms. Quantifying growth precisely is an important goal in microbiology. Growth dynamics are affected both by the doubling time of the microorganism and by any delay in growth upon transfer from one condition to another, the lag. The ScanLag method enables the characterization of these two independent properties at the level of colonies originating each from a single cell, generating a two-dimensional distribution of the lag time and of the growth time. In ScanLag, measurement of the time it takes for colonies on conventional nutrient agar plates to be detected is automated on an array of commercial scanners controlled by an in house application. Petri dishes are placed on the scanners, and the application acquires images periodically. Automated analysis of colony growth is then done by an application that returns the appearance time and growth rate of each colony. Other parameters, such as the shape, texture and color of the colony, can be extracted for multidimensional mapping of sub-populations of cells. Finally, the method enables the retrieval of rare variants with specific growth phenotypes for further characterization. The technique could be applied in bacteriology for the identification of long lag that can cause persistence to antibiotics, as well as a general low cost technique for phenotypic screens.     

Growing Yeast into Cylindrical Colonies

Microorganisms often form complex multicellular assemblies such as biofilms and colonies. Understanding the interplay between assembly expansion, metabolic yield, and nutrient diffusion within a freely growing colony remains a challenge. Most available data on microorganisms are from planktonic cultures, due to the lack of experimental tools to control the growth of multicellular assemblies. Here, we propose a method to constrain the growth of yeast colonies into simple geometric shapes such as cylinders. To this end, we designed a simple, versatile culture system to control the location of nutrient delivery below a growing colony. Under such culture conditions, yeast colonies grow vertically and only at the locations where nutrients are delivered. Colonies increase in height at a steady growth rate that is inversely proportional to the cylinder radius. We show that the vertical growth rate of cylindrical colonies is not defined by the single-cell division rate, but rather by the colony metabolic yield. This contrasts with cells in liquid culture, in which the single-cell division rate is the only parameter that defines the population growth rate. This method also provides a direct, simple method to estimate the metabolic yield of a colony. Our study further demonstrates the importance of the shape of colonies on setting their expansion. We anticipate that our approach will be a starting point for elaborate studies of the population dynamics, evolution, and ecology of microbial colonies in complex landscapes.     

Growing Yeast into Cylindrical Colonies

Microorganisms often form complex multicellular assemblies such as biofilms and colonies. Understanding the interplay between assembly expansion, metabolic yield, and nutrient diffusion within a freely growing colony remains a challenge. Most available data on microorganisms are from planktonic cultures, due to the lack of experimental tools to control the growth of multicellular assemblies. Here, we propose a method to constrain the growth of yeast colonies into simple geometric shapes such as cylinders. To this end, we designed a simple, versatile culture system to control the location of nutrient delivery below a growing colony. Under such culture conditions, yeast colonies grow vertically and only at the locations where nutrients are delivered. Colonies increase in height at a steady growth rate that is inversely proportional to the cylinder radius. We show that the vertical growth rate of cylindrical colonies is not defined by the single-cell division rate, but rather by the colony metabolic yield. This contrasts with cells in liquid culture, in which the single-cell division rate is the only parameter that defines the population growth rate. This method also provides a direct, simple method to estimate the metabolic yield of a colony. Our study further demonstrates the importance of the shape of colonies on setting their expansion. We anticipate that our approach will be a starting point for elaborate studies of the population dynamics, evolution, and ecology of microbial colonies in complex landscapes.     

Microbial Community Structure of Leaf-Cutter Ant Fungus Gardens and Refuse Dumps

Background

Leaf-cutter ants use fresh plant material to grow a mutualistic fungus that serves as the ants'' primary food source. Within fungus gardens, various plant compounds are metabolized and transformed into nutrients suitable for ant consumption. This symbiotic association produces a large amount of refuse consisting primarily of partly degraded plant material. A leaf-cutter ant colony is thus divided into two spatially and chemically distinct environments that together represent a plant biomass degradation gradient. Little is known about the microbial community structure in gardens and dumps or variation between lab and field colonies.

Methodology/Principal Findings

Using microbial membrane lipid analysis and a variety of community metrics, we assessed and compared the microbiota of fungus gardens and refuse dumps from both laboratory-maintained and field-collected colonies. We found that gardens contained a diverse and consistent community of microbes, dominated by Gram-negative bacteria, particularly γ-Proteobacteria and Bacteroidetes. These findings were consistent across lab and field gardens, as well as host ant taxa. In contrast, dumps were enriched for Gram-positive and anaerobic bacteria. Broad-scale clustering analyses revealed that community relatedness between samples reflected system component (gardens/dumps) rather than colony source (lab/field). At finer scales samples clustered according to colony source.

Conclusions/Significance

Here we report the first comparative analysis of the microbiota from leaf-cutter ant colonies. Our work reveals the presence of two distinct communities: one in the fungus garden and the other in the refuse dump. Though we find some effect of colony source on community structure, our data indicate the presence of consistently associated microbes within gardens and dumps. Substrate composition and system component appear to be the most important factor in structuring the microbial communities. These results thus suggest that resident communities are shaped by the plant degradation gradient created by ant behavior, specifically their fungiculture and waste management.     

Coupled oscillators and activity waves in ant colonies

We investigated the phenomenon of activity cycles in ants, taking into account the spatial structure of colonies. In our study species, Leptothorax acervorum, there are two spatially segregated groups in the nest. We developed a model that considers the two groups as coupled oscillators which can produce synchronized activity. By investigating the effects of noise on the model system we predicted how the return of foragers affects activity cycles in ant colonies. We tested these predictions empirically by comparing the activity of colonies under two conditions: when foragers are and are not allowed to return to the nest. The activity of the whole colony and of each group within the colony was studied using image analysis. This allowed us to reveal the spatial pattern of activity wave propagation in ant colonies for the first time.     

Evaluation of counting error due to colony masking in bioaerosol sampling.

Colony counting error due to indistinguishable colony overlap (i.e., masking) was evaluated theoretically and experimentally. A theoretical model to predict colony masking was used to determine colony counting efficiency by Monte Carlo computer simulation of microorganism collection and development into CFU. The computer simulation was verified experimentally by collecting aerosolized Bacillus subtilis spores and examining micro- and macroscopic colonies. Colony counting efficiency decreased (i) with increasing density of collected culturable microorganisms, (ii) with increasing colony size, and (iii) with decreasing ability of an observation system to distinguish adjacent colonies as separate units. Counting efficiency for 2-mm colonies, at optimal resolution, decreased from 98 to 85% when colony density increased from 1 to 10 microorganisms cm-2, in contrast to an efficiency decrease from 90 to 45% for 5-mm colonies. No statistically significant difference (alpha = 0.05) between experimental and theoretical results was found when colony shape was used to estimate the number of individual colonies in a CFU. Experimental colony counts were 1.2 times simulation estimates when colony shape was not considered, because of nonuniformity of actual colony size and the better discrimination ability of the human eye relative to the model. Colony surface densities associated with high counting accuracy were compared with recommended upper plate count limits and found to depend on colony size and an observation system's ability to identify overlapped colonies. Correction factors were developed to estimate the actual number of collected microorganisms from observed colony counts.(ABSTRACT TRUNCATED AT 250 WORDS)     

Development of an agar lift-DNA/DNA hybridization technique for use in visualization of the spatial distribution of Eubacteria on soil surfaces.

While microbial growth is well-understood in pure culture systems, less is known about growth in intact soil systems. The objective of this work was to develop a technique to allow visualization of the two-dimensional spatial distribution of bacterial growth on a homogenous soil surface. This technique is a two-step process wherein an agar lift is taken and analyzed using a universal gene probe. An agar lift is comprised of a thin layer of soil that is removed from a soil surface using an agar slab. The agar is incubated to allow for microbial growth, after which, colonies are transferred to a membrane for conventional bacterial colony DNA/DNA hybridization analysis. In this study, a eubacterial specific probe was used to demonstrate that growing bacterial populations on soil surfaces could be visualized. Results show that microbial growth and distribution was nonuniform across the soil surface. Spot supplementation of the soil with benzoate or glucose resulted in a localized microbial growth response. Since only growing colonies are detected, this technique should facilitate a greater understanding of the microbial distribution and its response to substrate addition in more heterogenous soil systems.     

A novel method for exploring elemental composition of microbial communities: Laser ablation-inductively coupled plasma-mass spectrometry of intact bacterial colonies

Bacterial colonies are spatially complex structures whose physiology is profoundly dependent on interactions between cells and with the underlying semi-solid substratum. Here, we use bacterial colonies as a model of a microbial community to evaluate the potential of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to delineate elemental distributions within colonies with minimal pre-treatment. To reduce water content of the colony and limit undesirable absorption of laser energy, we compared methods of preparing 24 h-old colonies of Escherichia coli TG1 on agar for laser ablation. Colonies on excised agar segments dried on chromatography paper were superior to colonies dried in a dessicator or by prolonged incubation, with respect to signal magnitude, signal:noise ratio and background signal. Having optimised laser scan speed (10 μm s^− 1) and laser beam diameter (100 μm), further improvements were achieved by growing colonies on nylon membranes over agar, which were then transferred to the ablation chamber without further treatment. Repeated line rasters across individual membrane-supported colonies yielded three-dimensional elemental maps of colonies, revealing a convex morphology consistent with visual inspection. By normalising isotope counts for P, Mn, Zn, Fe and Ca against Mg, the most abundant cellular divalent cation, we sought elemental heterogeneity within the colony. The normalised concentration of Mn in the perimeter was higher than in the colony interior, whereas the converse was true for Ca. LA-ICP-MS is a novel and powerful method for probing elemental composition and organisation within microbial communities and should find numerous applications in, for example, biofilm studies.     

Automated counting of mammalian cell colonies by means of a flat bed scanner and image processing.

BACKGROUND: Clonogenic assays are used frequently to measure the cell killing and mutagenic effects of radiation and other agents. Clonogenic assays carried out manually are tedious and time-consuming and involve a significant element of subjectivity. However, several commercial automatic colony counters are available. Based on CCD video imaging and image analysis they are relatively expensive and can analyze only one petri dish at a time. METHOD: We have developed a cheaper and more efficient device, which employs a flat bed scanner to image 12 60-mm petri dishes at a time. Two major problems in automated colony counting are the clustering of colonies and edge effects. By using standard image analysis and implementing an inflection point algorithm, these problems were greatly diminished. The resulting system was compared with two manual colony counts, as well as with automated counts with the Oxford Optronix ColCount colony counter for cell lines V79 and HaCaT. RESULTS: Comparisons assuming the manual counts to be correct showed that our automatic counter was slightly more accurate than the commercial unit. CONCLUSIONS: As a whole, our automated colony counter performed significantly better than the commercial unit with regard to processing time, cost and accuracy.