RESUMEN
The rhizosphere context of inulin-accumulating plants, such as Jerusalem artichoke (Helianthus tuberosus), is an ideal starting basis for the discovery of inulolytic enzymes with potential for bio fructose production. We isolated a Glutamicibacter mishrai NJAU-1 strain from this context, showing exo-inulinase activity, releasing fructose from fructans. The growth conditions (pH 9.0; 15 °C) were adjusted, and the production of inulinase by Glutamicibacter mishrai NJAU-1 increased by 90% (0.32 U/mL). Intriguingly, both levan and inulin, but not fructose and sucrose, induced the production of exo-inulinase activity. Two exo-inulinase genes (inu1 and inu2) were cloned and heterologously expressed in Pichia pastoris. While INU2 preferentially hydrolyzed longer inulins, the smallest fructan 1-kestose appeared as the preferred substrate for INU1, also efficiently degrading nystose and sucrose. Active site docking studies with GFn- and Fn-type small inulins (G is glucose, F is fructose, and n is the number of ß (2-1) bound fructose moieties) revealed subtle substrate differences between INU1 and INU2. A possible explanation about substrate specificity and INU's protein structure is then suggested. KEY POINTS: ⢠A Glutamicibacter mishrai strain harbored exo-inulinase activity. ⢠Fructans induced the inulolytic activity in G. mishrai while the inulolytic activity was optimized at pH 9.0 and 15 °C. ⢠Two exo-inulinases with differential substrate specificity were characterized.
Asunto(s)
Helianthus , Fructanos , Fructosa , Glicósido Hidrolasas , Inulina , SacarosaRESUMEN
The intensity, frequency, duration, and contribution of distinct PM2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM2.5 and PM1 monitoring using novel low-cost sensing (LCS) devices, AS-LUNG. GRIMM-comparable observations were acquired by the corrected AS-LUNG readings, with R2 up to 0.998. Twenty-six non-smoking healthy adults were recruited in Taiwan in 2018 for 7-day personal, home indoor, and home outdoor PM monitoring. The results showed 5-min PM2.5 and PM1 exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m3 , respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM2.5 increments of 76.5 and 183.8 µg/m3 (1 min), respectively. Incense burning had the highest mean PM2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5-min PM2.5 increments (15.0 µg/m3 ) to indoor levels, among all single sources. Certain events accounted for 14.0%-39.6% of subjects' daily exposures. With the high resolution of AS-LUNG data and detailed time-activity diaries, the impacts of sources and ventilations were assessed in detail.
Asunto(s)
Contaminación del Aire Interior/estadística & datos numéricos , Exposición a Riesgos Ambientales/estadística & datos numéricos , Monitoreo del Ambiente/instrumentación , Material Particulado , Adulto , Contaminantes Atmosféricos , Culinaria , Monitoreo del Ambiente/métodos , Humanos , Tamaño de la Partícula , Estaciones del Año , Taiwán , VentilaciónRESUMEN
To tackle the challenge of the data accuracy issues of low-cost sensors (LCSs), the objective of this work was to obtain robust correction equations to convert LCS signals into data comparable to that of research-grade instruments using side-by-side comparisons. Limited sets of seed LCS devices, after laboratory evaluations, can be installed strategically in areas of interest without official monitoring stations to enable reading adjustments of other uncalibrated LCS devices to enhance the data quality of sensor networks. The robustness of these equations for LCS devices (AS-LUNG with PMS3003 sensor) under a hood and a chamber with two different burnt materials and before and after 1.5 years of field campaigns were evaluated. Correction equations with incense or mosquito coils burning inside a chamber with segmented regressions had a high R2 of 0.999, less than 6.0% variability in the slopes, and a mean RMSE of 1.18 µg/m3 for 0.1-200 µg/m3 of PM2.5, with a slightly higher RMSE for 0.1-400 µg/m3 compared to EDM-180. Similar results were obtained for PM1, with an upper limit of 200 µg/m3. Sensor signals drifted 19-24% after 1.5 years in the field. Practical recommendations are given to obtain equations for Federal-Equivalent-Method-comparable measurements considering variability and cost.