Complex axial growth patterns in an early Cambrian trilobite from South Australia

The exceptional fossil record of trilobites provides our best window on developmental processes in early euarthropods, but data on growth dynamics are limited. Here, we analyse post-embryonic axial growth in the Cambrian trilobite Estaingia bilobata from the Emu Bay Shale, South Australia. Using threshold models, we show that abrupt changes in growth trajectories of different body sections occurred in two phases, closely associated with the anamorphic/epimorphic and meraspid/holaspid transitions. These changes are similar to the progression to sexual maturity seen in certain extant euarthropods and suggest that the onset of maturity coincided with the commencement of the holaspid period. We also conduct hypothesis testing to reveal the likely controls of observed axial growth gradients and suggest that size may better explain growth patterns than moult stage. The two phases of allometric change in E. bilobata , as well as probable differing growth regulation in the earliest post-embryonic stages, suggest that observed body segmentation patterns in this trilobite were the result of a complex series of changing growth controls that characterized different ontogenetic intervals. This indicates that trilobite development is more complex than previously thought, even in early members of the clade.

Rapid Simultaneous Testing of Multiple Antibiotics by the MALDI-TOF MS Direct-on-Target Microdroplet Growth Assay

Accelerating antimicrobial susceptibility testing (AST) is a priority in the development of novel microbiological methods. The MALDI-TOF MS-based direct-on-target microdroplet growth assay (DOT-MGA) has recently been described as a rapid phenotypic AST method. In this proof-of-principle study, we expanded this method to simultaneously test 24 antimicrobials. An Enterobacterales panel was designed and evaluated using 24 clinical isolates. Either one or two (only for antimicrobials with the EUCAST “I” category) breakpoint concentrations were tested. Microdroplets containing bacterial suspensions with antimicrobials and growth controls were incubated directly on the spots of a disposable MALDI target inside a humidity chamber for 6, 8 or 18 h. Broth microdilution was used as the standard method. After 6 and 8 h of incubation, the testing was valid (i.e., growth control was successfully detected) for all isolates and the overall categorical agreement was 92.0% and 92.7%, respectively. Although the overall assay performance applying short incubation times is promising, the lower performance with some antimicrobials and when using the standard incubation time of 18 h indicates the need for thorough standardization of assay conditions. While using “homebrew” utensils and provisional evaluation algorithms here, technical solutions such as dedicated incubation chambers, tools for broth removal and improved software analyses are needed.

Varied Contribution of Phospholipid Shedding From Membrane to Daptomycin Tolerance in Staphylococcus aureus

It has been suggested that daptomycin can be inactivated by lipids released by Staphylococcus aureus and that this effect is antagonized by phenol soluble modulins (PSMs), which bind to the shed lipids. PSM production is regulated by the Agr system, and others have shown that loss of the Agr function enhances S. aureus survival in the presence of daptomycin. Here we assessed the impact of Agr function on daptomycin activity and lipid metabolism under various conditions. Daptomycin activity was evaluated against three sets of isogenic strain series with wild-type or dysfunctional Agr using static daptomycin time-kills over 24 h and against one strain pair using in vitro pharmacokinetic/pharmacodynamic (PK/PD) models simulating clinical daptomycin exposure for 48 h. We performed comprehensive lipidomics on bacterial membranes and the spent media to correlate lipid shedding with survival. In static time-kill experiments, two agr-deficient strains (SH1000- and USA300 LAC ΔagrA) showed improved survival for 8 h compared with their corresponding wild-type strains as seen in previous studies, but this difference did not persist for 24 h. However, four other agr-deficient strains (SH1001 and JE2 agr KOs) did not demonstrate improved survival compared to isogenic wild-type strains at any time in the time-kills. Lipidomics analysis of SH1000, SH1001, and SH1000- strains showed daptomycin exposure increased lipid shedding compared to growth controls in all strains with phosphatidylglycerols (PGs), lysylPGs and cardiolipins predominating. In the cell pellets, PGs and lysylPGs decreased but cardiolipins were unchanged with daptomycin exposure. The shed lipid profiles in SH1001 and SH1000- were similar, suggesting that the inability to resist daptomycin by SH1001 was not because of differences in lipid shedding. In the PK/PD model, the agr mutant SH1000- strain did not show improved survival relative to SH1000 either. In conclusion, inactivation of daptomycin by shed lipids may be dependent on genetic background, the specific agr mutations, or the techniques used to generate these KOs rather than the overall function of the Agr system, and its contribution to daptomycin tolerance seems to be varied, transient, and growth-condition dependent.

An IoT based Application for Real Time Monitoring of the Crops for Agriculture Lands

The Internet of Things (IoT) provides the opportunity of individuals and devices to educate and collaborate with lots of things namely sensors, actuators, appliances and other wirelessly connected things and we proposed an idea to implement IoT in Agriculture. Environmental attributes are measured using sensors. Regarding our survey, we came to know that website is used as an interface, linked to the sensed data. Uses local Database and services which makes app huge. Lags Disease detection and other predictions are not done. Our project generates data in real time and predict the problems, gives early cautioning and prevent interlude, develop new opportunities and plan better Agri-lands for the future by using simulations. Predicts crop diseases and gives preventive measures. Forecasts the climatic conditions like humidity, rainfall and manage the irrigation, checks soil fertility, monitors water quality for optimal plant growth, controls water usage and irrigation management.