Mining for novel cyclomaltodextrin glucanotransferases unravels the carbohydrate metabolism pathway via cyclodextrins in Thermoanaerobacterales.

Carbohydrate metabolism via cyclodextrins (CM-CD) is an uncommon starch-converting pathway that thoroughly depends on extracellular cyclomaltodextrin glucanotransferases (CGTases) to transform the surrounding starch substrate to α-(1,4)-linked oligosaccharides and cyclodextrins (CDs). The CM-CD pathway has emerged as a convenient microbial adaptation to thrive under extreme temperatures, as CDs are functional amphipathic toroids with higher heat-resistant values than linear dextrins. Nevertheless, although the CM-CD pathway has been described in a few mesophilic bacteria and archaea, it remains obscure in extremely thermophilic prokaryotes (Topt ≥ 70 °C). Here, a new monophyletic group of CGTases with an exceptional three-domain ABC architecture was detected by (meta)genome mining of extremely thermophilic Thermoanaerobacterales living in a wide variety of hot starch-poor environments on Earth. Functional studies of a representative member, CldA, showed a maximum activity in a thermoacidophilic range (pH 4.0 and 80 °C) with remarkable product diversification that yielded a mixture of α:ß:γ-CDs (34:62:4) from soluble starch, as well as G3-G7 linear dextrins and fermentable sugars as the primary products. Together, comparative genomics and predictive functional analysis, combined with data of the functionally characterized key proteins of the gene clusters encoding CGTases, revealed the CM-CD pathway in Thermoanaerobacterales and showed that it is involved in the synthesis, transportation, degradation, and metabolic assimilation of CDs.

Developing a new wireless sensor network platform and its application in precision agriculture.

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of "smart dust" offer great advantages due to their small size, low power consumption, easy integration and support for "green" applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network.