Cultivation and functional characterization of 79 planctomycetes uncovers their unique biology

When it comes to the discovery and analysis of yet uncharted bacterial traits, pure cultures are essential as only these allow detailed morphological and physiological characterization as well as genetic manipulation. However, microbiologists are struggling to isolate and maintain the majority of bacterial strains, as mimicking their native environmental niches adequately can be a challenging task. Here, we report the diversity-driven cultivation, characterization and genome sequencing of 79 bacterial strains from all major taxonomic clades of the conspicuous bacterial phylum Planctomycetes. The samples were derived from different aquatic environments but close relatives could be isolated from geographically distinct regions and structurally diverse habitats, implying that 'everything is everywhere'. With the discovery of lateral budding in 'Kolteria novifilia' and the capability of the members of the Saltatorellus clade to divide by binary fission as well as budding, we identified previously unknown modes of bacterial cell division. Alongside unobserved aspects of cell signalling and small-molecule production, our findings demonstrate that exploration beyond the well-established model organisms has the potential to increase our knowledge of bacterial diversity. We illustrate how 'microbial dark matter' can be accessed by cultivation techniques, expanding the organismic background for small-molecule research and drug-target detection.

[Validation of the prehospital mSTaRT triage algorithm. A pilot study for the development of a multicenter evaluation]

INTRODUCTION

Successful management of a mass casualty incident requires integrated operating procedures. A common division of victims into descriptive needs-based groups and the corresponding decision processes is the key to ensuring a successful operational response. The mSTaRT ("modified simple triage and rapid treatment") algorithm should enable emergency medical technicians to conduct triage, perform appropriate medical interventions, and coordinate transportation to adequate care facilities. The aim of this study was to design a concept to validate the mSTaRT algorithm.

METHODS

Standardized evaluation sheets were distributed to emergency medical services (EMS) staff to prospectively classify trauma patients according to the mSTaRT algorithm: red (immediate: critically injured patients who can be helped by immediate transport), yellow (urgent: severely injured patients whose transport can be delayed), or green (delayed: patients with minor injuries who need help less urgently). The patients were then reevaluated in the emergency department, and the results were compared. The main points of the comparison were consistency of triage category and rates of overtriage and undertriage.

RESULTS

The study included 151 trauma patients. Of these, 62.3% were triaged correctly, 10.6% were overtriaged (2.6% critical overtriage), and 27.1% were undertriaged (4.0% critical undertriage). In the critically injured (immediate) category, the positive likelihood ratio (LR+) was 17.3 (95% CI 3.8-795), and the negative likelihood ratio (LR-) was 0.51 (95% CI 0.22-0.83). The probability of identifying a critically injured (immediate) patient was 17.3 times higher than the probability of identifying a severely (urgent) or minor (delayed) injured patient as immediate. Therefore, the rate of overtriage was very low. But every second patient who should have been classified as immediate was undertriaged by the EMS personnel. This undertriage was due to patients' suffering from head trauma, a well-known problem in the clinical context but a new problem in the triage context.

CONCLUSION

The results of our pilot study show that by using mSTaRT, patients designated as yellow (urgent) and green (delayed) will be accurately distinguished from red (immediate) patients; therefore, only a small number of patients will be overtriaged as red. However, some patients with severe head injury may not be initially assigned to the red category as required, resulting in undertriage. Consequently, modification of the mSTaRT procedures should be considered. A further identifier in the algorithm or checkpoint in the process should act as a safety net for catching severe head injury. A larger data set is required to further validate the mSTaRT algorithm. This will be acquired by means of a multicenter study.